TY - JOUR
AB - A frameless stereotactic localization method with DSA is introduced in this paper. A locating plate and four head marks are used in the method. Using two projection images of DSA, the three dimension coordinate of any point can be calculated referring to the reference locating coordinate system. The method is the theoretic basis of locating brain structure such as the blood vessel using DSA.
AD - Biomedical Engineering Institute, Shanghai Jiaotong University.
AN - 11189256
AU - Fei, B.
AU - Zhuang, T.
DA - Jul
DP - Nlm
ET - 1997/07/01
KW - Algorithms
Angiography, Digital Subtraction/ instrumentation
Computer Simulation
Stereotaxic Techniques
LA - chi
M1 - 4
N1 - Fei, B
Zhuang, T
English Abstract
China
Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation
Zhongguo Yi Liao Qi Xie Za Zhi. 1997 Jul;21(4):207-10.
PY - 1997
SN - 1671-7104 (Print)
1671-7104 (Linking)
SP - 207-10
ST - [The study of a frameless stereotactic localization method using DSA]
T2 - Zhongguo Yi Liao Qi Xie Za Zhi
TI - [The study of a frameless stereotactic localization method using DSA]
VL - 21
ID - 311
ER -
TY - JOUR
AB - The methodology and the state of the art of Computer-Assisted Surgery (CAS) are introduced in this paper. Computer-assisted surgery is a new high technology which uses computer science, biomedical engineering, mechanism, mathematics, surgery, and so on. Its objective is to help surgeons use multimodal data, such as CT, MRI, DSA, PET, et al. in a rational and quantitative way in order to plan and perform medical intervention. Stereotactic localization method and registration are two cruxes in computer-assisted surgery. There are several methods for localization and registration. In recent ten years, computer-assisted surgery has been a cynosure of scientists. Some computer-assisted surgery systems have been used in clinical practice.
AD - Biomedical Engineering Institute, Shanghai Jiaotong University, Shanghai 200030.
AN - 12548915
AU - Fei, B.
AU - Zhuang, T.
DA - Jun
DP - Nlm
ET - 2003/01/29
KW - General Surgery/methods
Image Processing, Computer-Assisted
Robotics
Therapy, Computer-Assisted/methods
LA - chi
M1 - 2
N1 - Fei, B
Zhuang, T
English Abstract
Review
China
Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 1998 Jun;15(2):195-202.
PY - 1998
SN - 1001-5515 (Print)
1001-5515 (Linking)
SP - 195-202
ST - [The method and development of computer-assisted surgery]
T2 - Sheng Wu Yi Xue Gong Cheng Xue Za Zhi
TI - [The method and development of computer-assisted surgery]
VL - 15
ID - 310
ER -
TY - JOUR
AB - The goal of this research is to register real-time interventional magnetic resonance imaging (iMRI) slice images with a previously obtained high-resolution MRI image volume, which in turn can be registered with functional images such as those from SPECT. The immediate application is in iMRI-guided treatment of prostate cancer, where additional images are desired to improve tumor targeting. In this article, simulation experiments are performed to demonstrate the feasibility of slice-to-volume registration for this application. We acquired 3D volume images from a 1.5-T MRI system and simulated low-field iMRI image slices by creating thick slices and adding noise. We created a slice-to-volume mutual information registration algorithm with special features to improve robustness. Features included a multiresolution approach, two similarity measures, and automatic restarting to avoid local minima. To assess the quality of registration, we calculated 3D displacements on a voxel-by-voxel basis over a volume of interest between slice-to-volume registration and volume-to-volume registration, which was previously shown to be quite accurate. More than 800 registration experiments were performed on MR images of three volunteers. The slice-to-volume registration algorithm was very robust and accurate for transverse slice images covering the prostate, with a registration error of only 0.4 +/- 0.2 mm. Error was greater at other slice orientations and positions. The automatic slice-to-volume mutual information registration algorithm is robust and probably sufficiently accurate to aid in iMRI-guided treatment of prostate cancer.
AD - Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio 44106, USA.
AN - 12582978
AU - Fei, B.
AU - Duerk, J. L.
AU - Wilson, D. L.
DO - 10.1002/igs.10052 [doi]
DP - Nlm
ET - 2003/02/13
KW - Algorithms
Computer Simulation
Feasibility Studies
Humans
Imaging, Three-Dimensional/ methods
Magnetic Resonance Imaging/ methods
Male
Minimally Invasive Surgical Procedures
Prostatic Neoplasms/ pathology
L1 - internal-pdf://3801954390/Fei-2002-Automatic 3D registration for interve.pdf
LA - eng
M1 - 5
N1 - Fei, Baowei
Duerk, Jeffrey L
Wilson, David L
R01-CA84433-01/CA/NCI NIH HHS/United States
R33-CA88144-01/CA/NCI NIH HHS/United States
Research Support, U.S. Gov't, Non-P.H.S.
Research Support, U.S. Gov't, P.H.S.
United States
Computer aided surgery : official journal of the International Society for Computer Aided Surgery
Comput Aided Surg. 2002;7(5):257-67.
PY - 2002
SN - 1092-9088 (Print)
1092-9088 (Linking)
SP - 257-67
ST - Automatic 3D registration for interventional MRI-guided treatment of prostate cancer
T2 - Comput Aided Surg
TI - Automatic 3D registration for interventional MRI-guided treatment of prostate cancer
UR - http://informahealthcare.com/doi/pdfplus/10.3109/10929080209146034
VL - 7
ID - 309
ER -
TY - JOUR
AB - A three-dimensional (3D) mutual information registration method was created and used to register MRI volumes of the pelvis and prostate. It had special features to improve robustness. First, it used a multi-resolution approach and performed registration from low to high resolution. Second, it used two similarity measures, correlation coefficient at lower resolutions and mutual information at full resolution, because of their particular advantages. Third, we created a method to avoid local minima by restarting the registration with randomly perturbed parameters. The criterion for restarting was a correlation coefficient below an empirically determined threshold. Experiments determined the accuracy of registration under conditions found in potential applications in prostate cancer diagnosis, staging, treatment and interventional MRI (iMRI) guided therapies. Images were acquired in the diagnostic (supine) and treatment position (supine with legs raised). Images were also acquired as a function of bladder filling and the time interval between imaging sessions. Overall studies on three patients and three healthy volunteers, when both volumes in a pair were obtained in the diagnostic position under comparable conditions, bony landmarks and prostate 3D centroids were aligned within 1.6 +/- 0.2 mm and 1.4 +/- 0.2 mm, respectively, values only slightly larger than a voxel. Analysis suggests that actual errors are smaller because of the uncertainty in landmark localization and prostate segmentation. Between the diagnostic and treatment positions, bony landmarks continued to register well, but prostate centroids moved towards the posterior 2.8-3.4 mm. Manual cropping to remove voxels in the legs was necessary to register these images. In conclusion, automatic, rigid body registration is probably sufficiently accurate for many applications in prostate cancer. For potential iMRI-guided treatments, the small prostate displacement between the diagnostic and treatment positions can probably be avoided by acquiring volumes in similar positions and by reducing bladder and rectal volumes.
AD - Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH 44106, USA.
AN - 11931473
AU - Fei, B.
AU - Wheaton, A.
AU - Lee, Z.
AU - Duerk, J. L.
AU - Wilson, D. L.
DA - Mar 7
DP - Nlm
ET - 2002/04/05
KW - Algorithms
Humans
Magnetic Resonance Imaging/ methods
Male
Models, Statistical
Pelvis/ pathology
Prostate/ pathology
Prostatic Neoplasms/ therapy
Radiometry/ methods
LA - eng
M1 - 5
N1 - Fei, Baowei
Wheaton, Andrew
Lee, Zhenghong
Duerk, Jeffrey L
Wilson, David L
R01-CA84433-01/CA/NCI NIH HHS/United States
R33-CA88144-01/CA/NCI NIH HHS/United States
Research Support, U.S. Gov't, P.H.S.
England
Physics in medicine and biology
Phys Med Biol. 2002 Mar 7;47(5):823-38.
PY - 2002
SN - 0031-9155 (Print)
0031-9155 (Linking)
SP - 823-38
ST - Automatic MR volume registration and its evaluation for the pelvis and prostate
T2 - Phys Med Biol
TI - Automatic MR volume registration and its evaluation for the pelvis and prostate
UR - http://iopscience.iop.org/0031-9155/47/5/309/
VL - 47
ID - 308
ER -
TY - JOUR
AB - In this study, we registered live-time interventional magnetic resonance imaging (iMRI) slices with a previously obtained high-resolution MRI volume that in turn can be registered with a variety of functional images, e.g., PET, SPECT, for tumor targeting. We created and evaluated a slice-to-volume (SV) registration algorithm with special features for its potential use in iMRI-guided radio-frequency (RF) thermal ablation of prostate cancer. The algorithm features included a multiresolution approach, two similarity measures, and automatic restarting to avoid local minima. Imaging experiments were performed on volunteers using a conventional 1.5-T MR scanner and a clinical 0.2-T C-arm iMRI system under realistic conditions. Both high-resolution MR volumes and actual iMRI image slices were acquired from the same volunteers. Actual and simulated iMRI images were used to test the dependence of SV registration on image noise, receive coil inhomogeneity, and RF needle artifacts. To quantitatively assess registration, we calculated the mean voxel displacement over a volume of interest between SV registration and volume-to-volume registration, which was previously shown to be quite accurate. More than 800 registration experiments were performed. For transverse image slices covering the prostate, the SV registration algorithm was 100% successful with an error of <2 mm, and the average and standard deviation was only 0.4 mm +/- 0.2 mm. Visualizations such as combined sector display and contour overlay showed excellent registration of the prostate and other organs throughout the pelvis. Error was greater when an image slice was obtained at other orientations and positions, mostly because of inconsistent image content such as that from variable rectal and bladder filling. These preliminary experiments indicate that MR SV registration is sufficiently accurate to aid image-guided therapy.
AD - Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH 44106, USA.
AN - 12774897
AU - Fei, B.
AU - Duerk, J. L.
AU - Boll, D. T.
AU - Lewin, J. S.
AU - Wilson, D. L.
DA - Apr
DO - 10.1109/TMI.2003.809078 [doi]
DP - Nlm
ET - 2003/05/31
KW - Algorithms
Artifacts
Catheter Ablation/ methods
Computer Simulation
Humans
Imaging, Three-Dimensional/methods
Magnetic Resonance Imaging/methods
Male
Monitoring, Intraoperative/methods
Prostatic Neoplasms/ diagnosis/ surgery
Reproducibility of Results
Sensitivity and Specificity
Subtraction Technique
Surgery, Computer-Assisted/ methods
LA - eng
M1 - 4
N1 - Fei, Baowei
Duerk, Jeffrey L
Boll, Daniel T
Lewin, Jonathan S
Wilson, David L
R01-CA84433-01/CA/NCI NIH HHS/United States
R33-CA88144-01/CA/NCI NIH HHS/United States
Comparative Study
Evaluation Studies
Research Support, U.S. Gov't, Non-P.H.S.
Research Support, U.S. Gov't, P.H.S.
Validation Studies
United States
IEEE transactions on medical imaging
IEEE Trans Med Imaging. 2003 Apr;22(4):515-25.
PY - 2003
SN - 0278-0062 (Print)
0278-0062 (Linking)
SP - 515-25
ST - Slice-to-volume registration and its potential application to interventional MRI-guided radio-frequency thermal ablation of prostate cancer
T2 - IEEE Trans Med Imaging
TI - Slice-to-volume registration and its potential application to interventional MRI-guided radio-frequency thermal ablation of prostate cancer
UR - http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=1200925
VL - 22
ID - 307
ER -
TY - JOUR
AB - A three-dimensional warping registration algorithm was created and compared to rigid body registration of magnetic resonance (MR) pelvic volumes including the prostate. The rigid body registration method combines the advantages of mutual information (MI) and correlation coefficient at different resolutions. Warping registration is based upon independent optimization of many interactively placed control points (CP's) using MI and a thin plate spline transformation. More than 100 registration experiments with 17 MR volume pairs determined the quality of registration under conditions simulating potential interventional MRI-guided treatments of prostate cancer. For image pairs that stress rigid body registration (e.g. supine, the diagnostic position, and legs raised, the treatment position), both visual and numerical evaluation methods showed that warping consistently worked better than rigid body. Experiments showed that approximately 180 strategically placed CP's were sufficiently expressive to capture important features of the deformation.
AD - Department of Biomedical Engineering, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH 44106, USA.
AN - 12631511
AU - Fei, B.
AU - Kemper, C.
AU - Wilson, D. L.
DA - Jul-Aug
DO - S0895611102000939 [pii]
DP - Nlm
ET - 2003/03/13
KW - Algorithms
Humans
Imaging, Three-Dimensional
Magnetic Resonance Imaging/ methods
Male
Models, Statistical
Pelvis/ pathology
Posture
Prostate/ pathology
Prostatic Neoplasms/ therapy
Radiometry/ methods
L1 - internal-pdf://2846564062/Fei-2003-A comparative study of warping and ri.pdf
LA - eng
M1 - 4
N1 - Fei, Baowei
Kemper, Corey
Wilson, David L
R01-CA84433-01/CA/NCI NIH HHS/United States
R33-CA88144-01/CA/NCI NIH HHS/United States
Comparative Study
Research Support, U.S. Gov't, Non-P.H.S.
Research Support, U.S. Gov't, P.H.S.
United States
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Comput Med Imaging Graph. 2003 Jul-Aug;27(4):267-81.
PY - 2003
SN - 0895-6111 (Print)
0895-6111 (Linking)
SP - 267-81
ST - A comparative study of warping and rigid body registration for the prostate and pelvic MR volumes
T2 - Comput Med Imaging Graph
TI - A comparative study of warping and rigid body registration for the prostate and pelvic MR volumes
UR - http://ac.els-cdn.com/S0895611102000939/1-s2.0-S0895611102000939-main.pdf?_tid=425432c0-c133-11e4-95be-00000aacb362&acdnat=1425338842_3c4972d7c33914de94ffff1125de8a32
VL - 27
ID - 306
ER -
TY - JOUR
AB - RATIONALE AND OBJECTIVES: Three-dimensional (3D) nonrigid image registration for potential applications in prostate cancer treatment and interventional magnetic resonance (iMRI) imaging-guided therapies were investigated. MATERIALS AND METHODS: An almost fully automated 3D nonrigid registration algorithm using mutual information and a thin plate spline (TPS) transformation for MR images of the prostate and pelvis were created and evaluated. In the first step, an automatic rigid body registration with special features was used to capture the global transformation. In the second step, local feature points (FPs) were registered using mutual information. An operator entered only five FPs located at the prostate center, left and right hip joints, and left and right distal femurs. The program automatically determined and optimized other FPs at the external pelvic skin surface and along the femurs. More than 600 control points were used to establish a TPS transformation for deformation of the pelvic region and prostate. Ten volume pairs were acquired from three volunteers in the diagnostic (supine) and treatment positions (supine with legs raised). RESULTS: Various visualization techniques showed that warping rectified the significant pelvic misalignment by the rigid-body method. Gray-value measures of registration quality, including mutual information, correlation coefficient, and intensity difference, all improved with warping. The distance between prostate 3D centroids was 0.7 +/- 0.2 mm after warping compared with 4.9 +/- 3.4 mm with rigid-body registration. CONCLUSION: Semiautomatic nonrigid registration works better than rigid-body registration when patient position is changed greatly between acquisitions. It could be a useful tool for many applications in the management of prostate.
AD - Department of Radiology, Case Western Reserve University and University Hospitals of Cleveland, 11100 Euclid Avenue, Cleveland, OH 44106, USA. baowei.fei@case.edu
AN - 16039535
AU - Fei, B.
AU - Duerk, J. L.
AU - Sodee, D. B.
AU - Wilson, D. L.
DA - Jul
DO - S1076-6332(05)00277-1 [pii]
10.1016/j.acra.2005.03.063 [doi]
DP - Nlm
ET - 2005/07/26
KW - Algorithms
Femur/pathology
Humans
Imaging, Three-Dimensional
Magnetic Resonance Imaging/ methods
Male
Pelvis/ pathology
Prostatic Neoplasms/ pathology/therapy
L1 - internal-pdf://0415434350/Fei-2005-Semiautomatic nonrigid registration f.pdf
LA - eng
M1 - 7
N1 - Fei, Baowei
Duerk, Jeffrey L
Sodee, D Bruce
Wilson, David L
R33-CA88144/CA/NCI NIH HHS/United States
Research Support, N.I.H., Extramural
Research Support, U.S. Gov't, Non-P.H.S.
Research Support, U.S. Gov't, P.H.S.
United States
Academic radiology
Acad Radiol. 2005 Jul;12(7):815-24.
PY - 2005
SN - 1076-6332 (Print)
1076-6332 (Linking)
SP - 815-24
ST - Semiautomatic nonrigid registration for the prostate and pelvic MR volumes
T2 - Acad Radiol
TI - Semiautomatic nonrigid registration for the prostate and pelvic MR volumes
UR - http://ac.els-cdn.com/S1076633205002771/1-s2.0-S1076633205002771-main.pdf?_tid=3ef685f6-c133-11e4-a312-00000aab0f01&acdnat=1425338837_8552b62667aa34e1d8727734539b9434
VL - 12
ID - 303
ER -
TY - JOUR
AB - In vivo small animal imaging provides a powerful tool for the study of a variety of diseases. Magnetic resonance imaging (MRI) has become an established technology for the assessment of therapies. In this study, we used high-resolution MRI to evaluate polycystic kidney disease (PKD) in transgenic mice. We used a customized mouse coil to acquire serial MR images from both wide-type and transgenic PKD mice immediately prior to, and 2-week and 4-week after therapy. We developed image segmentation, registration and visualization methods for this novel imaging application. We measured the kidney volumes for each mouse to assess the efficacy of the therapy. The segmentation results show that the kidney volumes are consistent, which are 348.7 ± 19.7 mm3for wild-type mice and 756.3 ± 44.1 mm3for transgenic mice, respectively. The image analysis methods provide a useful tool for this new application.
AD - Department of Radiology, Case Western Reserve University & University Hospitals of Cleveland, USA.
AN - 17282217
AU - Fei, B.
AU - Flask, C.
AU - Wang, H.
AU - Pi, A.
AU - Wilson, D.
AU - Shillingford, J.
AU - Murcia, N.
AU - Weimbs, T.
AU - Duerk, J.
DO - 10.1109/IEMBS.2005.1616448 [doi]
DP - Nlm
ET - 2007/02/07
LA - eng
N1 - Fei, Baowei
Flask, Chris
Wang, Hesheng
Pi, Ai
Wilson, David
Shillingford, Jonathan
Murcia, Noel
Weimbs, Thomas
Duerk, Jeffrey
United States
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference
Conf Proc IEEE Eng Med Biol Soc. 2005;1:467-9.
PY - 2005
SN - 1557-170X (Print)
1557-170X (Linking)
SP - 467-9
ST - Image Segmentation, Registration and Visualization of Serial MR Images for Therapeutic Assessment of Polycystic Kidney Disease in Transgenic Mice
T2 - Conf Proc IEEE Eng Med Biol Soc
TI - Image Segmentation, Registration and Visualization of Serial MR Images for Therapeutic Assessment of Polycystic Kidney Disease in Transgenic Mice
UR - http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=1616448
VL - 1
ID - 304
ER -
TY - JOUR
AB - This chapter describes automatic three-dimensional registration techniques for magnetic resonance images of carotid vessels. The immediate applications include atherosclerotic plaque characterization and plaque burden quantification vector-based segmentation using dark blood MR images having multiple contrast weightings (proton density (PD), T1, and T2). Another application is the measurement of disease progression and regression with drug trials. A normalized mutual information registration algorithm is applied to compensate movements between image acquisitions. PD, T1, and T2 images were acquired from patients and volunteers and then matched for image analysis. Visualization methods such as contour overlap showed that vessels well aligned after registration. Distance measurements from the landmarks indicated that the registration method worked well with an error of less than 1-mm.
AD - Case Western Reserve University, Cleveland, OH, USA.
AN - 15923750
AU - Fei, B.
AU - Suri, J. S.
AU - Wilson, D. L.
DP - Nlm
ET - 2005/06/01
LA - eng
N1 - Fei, Baowei
Suri, Jasjit S
Wilson, David L
Netherlands
Studies in health technology and informatics
Stud Health Technol Inform. 2005;113:394-411.
PY - 2005
SN - 0926-9630 (Print)
0926-9630 (Linking)
SP - 394-411
ST - Three-Dimensional Volume Registration of Carotid MR Images
T2 - Stud Health Technol Inform
TI - Three-Dimensional Volume Registration of Carotid MR Images
VL - 113
ID - 305
ER -
TY - JOUR
AB - We are investigating image processing and analysis techniques to improve the ability of dual-energy digital radiography (DR) for the detection of cardiac calcification. Computed tomography (CT) is an established tool for the diagnosis of coronary artery diseases. Dual-energy digital radiography could be a cost-effective alternative. In this study, we use three-dimensional (3D) CT images as the "gold standard" to evaluate the DR X-ray images for calcification detection. To this purpose, we developed an automatic registration method for 3D CT volumes and two-dimensional (2D) X-ray images. We call this 3D-to-2D registration. We first use a 3D CT image volume to simulate X-ray projection images and then register them with X-ray images. The registered CT projection images are then used to aid the interpretation dual-energy X-ray images for the detection of cardiac calcification. We acquired both CT and X-ray images from patients with coronary artery diseases. Experimental results show that the 3D-to-2D registration is accurate and useful for this new application.
AD - Dept. of Radiol. & Biomed. Eng., Case Western Reserve Univ., Cleveland, OH 44106, USA. baowei.fei@case.edu
AN - 17945687
AU - Fei, B.
AU - Chen, X.
AU - Wang, H.
AU - Sabol, J. M.
AU - DuPont, E.
AU - Gilkeson, R. C.
C2 - 2743908
DO - 10.1109/IEMBS.2006.259888 [doi]
DP - Nlm
ET - 2007/10/20
KW - Algorithms
Artificial Intelligence
Calcinosis/radiography
Coronary Angiography/ methods
Coronary Artery Disease/ radiography
Humans
Imaging, Three-Dimensional/ methods
Lung Diseases/radiography
Radiographic Image Enhancement/ methods
Radiography, Dual-Energy Scanned Projection/ methods
Reproducibility of Results
Sensitivity and Specificity
Subtraction Technique
Tomography, X-Ray Computed/ methods
L1 - internal-pdf://3720486403/Fei-2006-Automatic registration of CT volumes.pdf
LA - eng
N1 - Fei, Baowei
Chen, Xiang
Wang, Hesheng
Sabol, John M
DuPont, Elena
Gilkeson, Robert C
R21 CA120536/CA/NCI NIH HHS/United States
R21 CA120536-01/CA/NCI NIH HHS/United States
R21CA120536/CA/NCI NIH HHS/United States
Evaluation Studies
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
United States
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference
Nihms113523
Conf Proc IEEE Eng Med Biol Soc. 2006;1:1976-9.
PY - 2006
SN - 1557-170X (Print)
1557-170X (Linking)
SP - 1976-9
ST - Automatic registration of CT volumes and dual-energy digital radiography for detection of cardiac and lung diseases
T2 - Conf Proc IEEE Eng Med Biol Soc
TI - Automatic registration of CT volumes and dual-energy digital radiography for detection of cardiac and lung diseases
UR - http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2743908/pdf/nihms-113523.pdf
VL - 1
ID - 302
ER -
TY - JOUR
AB - We are investigating imaging techniques to study the tumor response to photodynamic therapy (PDT). Positron emission tomography (PET) can provide physiological and functional information. High-resolution magnetic resonance imaging (MRI) can provide anatomical and morphological changes. Image registration can combine MRI and PET images for improved tumor monitoring. In this study, we acquired high-resolution MRI and microPET 18F-fluorodeoxyglucose (FDG) images from C3H mice with RIF-1 tumors that were treated with Pc 4-based PDT. We developed two registration methods for this application. For registration of the whole mouse body, we used an automatic three-dimensional, normalized mutual information algorithm. For tumor registration, we developed a finite element model (FEM)-based deformable registration scheme. To assess the quality of whole body registration, we performed slice-by-slice review of both image volumes; manually segmented feature organs, such as the left and right kidneys and the bladder, in each slice; and computed the distance between corresponding centroids. Over 40 volume registration experiments were performed with MRI and microPET images. The distance between corresponding centroids of organs was 1.5 +/- 0.4 mm which is about 2 pixels of microPET images. The mean volume overlap ratios for tumors were 94.7% and 86.3% for the deformable and rigid registration methods, respectively. Registration of high-resolution MRI and microPET images combines anatomical and functional information of the tumors and provides a useful tool for evaluating photodynamic therapy.
AD - Department of Radiology, Case Western Reserve University and University Hospitals of Cleveland, Cleveland, Ohio 44106, USA. baowei.fei@case.edu
AN - 16878577
AU - Fei, B.
AU - Wang, H.
AU - Muzic, R. F., Jr.
AU - Flask, C.
AU - Wilson, D. L.
AU - Duerk, J. L.
AU - Feyes, D. K.
AU - Oleinick, N. L.
DA - Mar
DP - Nlm
ET - 2006/08/02
KW - Animals
Automation
Disease Models, Animal
Fluorodeoxyglucose F18/diagnostic use
Image Processing, Computer-Assisted/ methods
Imaging, Three-Dimensional
Kidney/pathology/radiography
Magnetic Resonance Imaging/ methods
Mice
Neoplasms/diagnosis/pathology/ radiography
Photochemotherapy/ methods
Positron-Emission Tomography/ methods
Reproducibility of Results
Sensitivity and Specificity
Time Factors
Urinary Bladder/pathology/radiography
Whole-Body Counting/veterinary
LA - eng
M1 - 3
N1 - Fei, Baowei
Wang, Hesheng
Muzic, Raymond F Jr
Flask, Chris
Wilson, David L
Duerk, Jeffrey L
Feyes, Denise K
Oleinick, Nancy L
5R24CA110943/CA/NCI NIH HHS/United States
Research Support, N.I.H., Extramural
Research Support, U.S. Gov't, Non-P.H.S.
United States
Medical physics
Med Phys. 2006 Mar;33(3):753-60.
PY - 2006
SN - 0094-2405 (Print)
0094-2405 (Linking)
SP - 753-60
ST - Deformable and rigid registration of MRI and microPET images for photodynamic therapy of cancer in mice
T2 - Med Phys
TI - Deformable and rigid registration of MRI and microPET images for photodynamic therapy of cancer in mice
VL - 33
ID - 301
ER -
TY - JOUR
AB - We are investigating three-dimensional (3D) to two-dimensional (2D) registration methods for computed tomography (CT) and dual-energy digital radiography (DR) for the detection of coronary artery calcification. CT is an established tool for the diagnosis of coronary artery diseases (CADs). Dual-energy digital radiography could be a cost-effective alternative for screening coronary artery calcification. In order to utilize CT as the "gold standard" to evaluate the ability of DR images for the detection and localization of calcium, we developed an automatic intensity-based 3D-to-2D registration method for 3D CT volumes and 2D DR images. To generate digital rendering radiographs (DRR) from the CT volumes, we developed three projection methods, i.e. Gaussian-weighted projection, threshold-based projection, and average-based projection. We tested normalized cross correlation (NCC) and normalized mutual information (NMI) as similarity measurement. We used the Downhill Simplex method as the search strategy. Simulated projection images from CT were fused with the corresponding DR images to evaluate the localization of cardiac calcification. The registration method was evaluated by digital phantoms, physical phantoms, and clinical data sets. The results from the digital phantoms show that the success rate is 100% with mean errors of less 0.8 mm and 0.2 degree for both NCC and NMI. The registration accuracy of the physical phantoms is 0.34 +/- 0.27 mm. Color overlay and 3D visualization of the clinical data show that the two images are registered well. This is consistent with the improvement of the NMI values from 0.20 +/- 0.03 to 0.25 +/- 0.03 after registration. The automatic 3D-to-2D registration method is accurate and robust and may provide a useful tool to evaluate the dual-energy DR images for the detection of coronary artery calcification.
AD - Case Western Reserve University and Xi'an Jiaotong University.
University Hospitals Case Medical Center.
Case Western Reserve University.
AN - 24386527
AU - Chen, X.
AU - Gilkeson, R.
AU - Fei, B.
C2 - 3877237
DA - Mar 3
DO - 10.1117/12.710192 [doi]
DP - Nlm
ET - 2007/03/03
LA - Eng
N1 - Chen, Xiang
Gilkeson, Robert
Fei, Baowei
R21 CA120536/CA/NCI NIH HHS/United States
Proceedings of SPIE
Nihms432054
Proc SPIE. 2007 Mar 3;6512. doi: 10.1117/12.710192.
PY - 2007
SN - 1996-756X (Print)
1996-756X (Linking)
ST - Automatic Intensity-based 3D-to-2D Registration of CT Volume and Dual-energy Digital Radiography for the Detection of Cardiac Calcification
T2 - Proc SPIE
TI - Automatic Intensity-based 3D-to-2D Registration of CT Volume and Dual-energy Digital Radiography for the Detection of Cardiac Calcification
UR - http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=1336654
VL - 6512
ID - 299
ER -
TY - JOUR
AB - We are investigating three-dimensional (3D) to two-dimensional (2D) registration methods for computed tomography (CT) and dual-energy digital radiography (DEDR). CT is an established tool for the detection of cardiac calcification. DEDR could be a cost-effective alternative screening tool. In order to utilize CT as the "gold standard" to evaluate the capability of DEDR images for the detection and localization of calcium, we developed an automatic, intensity-based 3D-to-2D registration method for 3D CT volumes and 2D DEDR images. To generate digitally reconstructed radiography (DRR) from the CT volumes, we developed several projection algorithms using the fast shear-warp method. In particular, we created a Gaussian-weighted projection for this application. We used normalized mutual information (NMI) as the similarity measurement. Simulated projection images from CT values were fused with the corresponding DEDR images to evaluate the localization of cardiac calcification. The registration method was evaluated by digital phantoms, physical phantoms, and clinical data sets. The results from the digital phantoms show that the success rate is 100% with a translation difference of less than 0.8 mm and a rotation difference of less than 0.2 degrees. For physical phantom images, the registration accuracy is 0.43 +/- 0.24 mm. Color overlay and 3D visualization of clinical images show that the two images registered well. The NMI values between the DRR and DEDR images improved from 0.21 +/- 0.03 before registration to 0.25 +/- 0.03 after registration. Registration errors measured from anatomic markers decreased from 27.6 +/- 13.6 mm before registration to 2.5 +/- 0.5 mm after registration. Our results show that the automatic 3D-to-2D registration is accurate and robust. This technique can provide a useful tool for correlating DEDR with CT images for screening coronary artery calcification.
AD - Department of Radiology, Case Western Reserve University, Cleveland, Ohio 44106, USA.
AN - 18196818
AU - Chen, X.
AU - Gilkeson, R. C.
AU - Fei, B.
C2 - 2743028
DA - Dec
DP - Nlm
ET - 2008/01/17
KW - Calcinosis/ radiography
Clinical Medicine
Coronary Artery Disease/radiography
Heart/radiography
Humans
Imaging, Three-Dimensional/ methods
Models, Theoretical
Phantoms, Imaging
Radiography, Dual-Energy Scanned Projection/ instrumentation
Tomography, X-Ray Computed/ instrumentation
L1 - internal-pdf://1937831465/Chen-2007-Automatic 3D-to-2D registration for.pdf
LA - eng
M1 - 12
N1 - Chen, Xiang
Gilkeson, Robert C
Fei, Baowei
CA110943/CA/NCI NIH HHS/United States
R21 CA120536/CA/NCI NIH HHS/United States
R21 CA120536-01/CA/NCI NIH HHS/United States
R21 CA120536-02/CA/NCI NIH HHS/United States
R21CA120536/CA/NCI NIH HHS/United States
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
United States
Medical physics
Nihms113518
Med Phys. 2007 Dec;34(12):4934-43.
PY - 2007
SN - 0094-2405 (Print)
0094-2405 (Linking)
SP - 4934-43
ST - Automatic 3D-to-2D registration for CT and dual-energy digital radiography for calcification detection
T2 - Med Phys
TI - Automatic 3D-to-2D registration for CT and dual-energy digital radiography for calcification detection
UR - http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2743028/pdf/nihms113518.pdf
VL - 34
ID - 295
ER -
TY - JOUR
AB - We are developing in vivo small animal imaging techniques that can measure early effects of photodynamic therapy (PDT) for prostate cancer. PDT is an emerging therapeutic modality that continues to show promise in the treatment of cancer. At our institution, a new second-generation photosensitizing drug, the silicon phthalocyanine Pc 4, has been developed and evaluated at the Case Comprehensive Cancer Center. In this study, we are developing magnetic resonance imaging (MRI) techniques that provide therapy monitoring and early assessment of tumor response to PDT. We generated human prostate cancer xenografts in athymic nude mice. For the imaging experiments, we used a high-field 9.4-T small animal MR scanner (Bruker Biospec). High-resolution MR images were acquired from the treated and control tumors pre- and post-PDT and 24 hr after PDT. We utilized multi-slice multi-echo (MSME) MR sequences. During imaging acquisitions, the animals were anesthetized with a continuous supply of 2% isoflurane in oxygen and were continuously monitored for respiration and temperature. After imaging experiments, we manually segmented the tumors on each image slice for quantitative image analyses. We computed three-dimensional T2 maps for the tumor regions from the MSME images. We plotted the histograms of the T2 maps for each tumor pre- and post-PDT and 24 hr after PDT. After the imaging and PDT experiments, we dissected the tumor tissues and used the histologic slides to validate the MR images. In this study, six mice with human prostate cancer tumors were imaged and treated at the Case Center for Imaging Research. The T2 values of treated tumors increased by 24 +/- 14% 24 hr after the therapy. The control tumors did not demonstrate significant changes of the T2 values. Inflammation and necrosis were observed within the treated tumors 24 hour after the treatment. Preliminary results show that Pc 4-PDT is effective for the treatment of human prostate cancer in mice. The small animal MR imaging provides a useful tool to evaluate early tumor response to photodynamic therapy in mice.
AD - Department of Radiology, Case Western Reserve University, University Hospitals of Cleveland, and the Case Comprehensive Cancer Center ; Department of Biomedical Engineering, Case Western Reserve University, University Hospitals of Cleveland, and the Case Comprehensive Cancer Center.
Department of Biomedical Engineering, Case Western Reserve University, University Hospitals of Cleveland, and the Case Comprehensive Cancer Center.
Department of Radiology, Case Western Reserve University, University Hospitals of Cleveland, and the Case Comprehensive Cancer Center.
Department of Radiation Oncology, Case Western Reserve University, University Hospitals of Cleveland, and the Case Comprehensive Cancer Center.
Department of Pathology, Case Western Reserve University, University Hospitals of Cleveland, and the Case Comprehensive Cancer Center.
AN - 24386525
AU - Fei, B.
AU - Wang, H.
AU - Chen, X.
AU - Meyers, J.
AU - Mulvihill, J.
AU - Feyes, D.
AU - Edgehouse, N.
AU - Duerk, J. L.
AU - Pretlow, T. G.
AU - Oleinick, N. L.
C2 - 3877221
DA - Mar 29
DO - 10.1117/12.708718 [doi]
DP - Nlm
ET - 2007/03/29
LA - Eng
N1 - Fei, Baowei
Wang, Hesheng
Chen, Xiang
Meyers, Joseph
Mulvihill, John
Feyes, Denise
Edgehouse, Nancy
Duerk, Jeffrey L
Pretlow, Thomas G
Oleinick, Nancy L
R21 CA120536/CA/NCI NIH HHS/United States
Proceedings of SPIE
Nihms432056
Proc SPIE. 2007 Mar 29;6511. doi: 10.1117/12.708718.
PY - 2007
SN - 1996-756X (Print)
1996-756X (Linking)
ST - Small Animal Imaging for Early Assessment of Therapeutic Efficacy of Photodynamic Therapy for Prostate Cancer
T2 - Proc SPIE
TI - Small Animal Imaging for Early Assessment of Therapeutic Efficacy of Photodynamic Therapy for Prostate Cancer
UR - http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=1336638
VL - 6511
ID - 297
ER -
TY - JOUR
AB - INTRODUCTION: High-field magnetic resonance imaging (MRI) is an emerging technique that provides a powerful, non-invasive tool for in vivo studies of cancer therapy in animal models. Photodynamic therapy (PDT) is a relatively new treatment modality for prostate cancer, the second leading cause of cancer mortality in American males. The goal of this study was to evaluate the response of human prostate tumor cells growing as xenografts in athymic nude mice to Pc 4-sensitized PDT. MATERIALS AND METHODS: PC-3, a cell line derived from a human prostate malignant tumor, was injected intradermally on the back flanks of athymic nude mice. Two tumors were initiated on each mouse. One was treated and the other served as the control. A second-generation photosensitizing drug Pc 4 (0.6 mg/kg body weight) was delivered to each animal by tail vein injection 48 hours before laser illumination (672 nm, 100 mW/cm(2), 150 J/cm(2)). A dedicated high-field (9.4 T) small-animal MR scanner was used for image acquisitions. A multi-slice multi-echo (MSME) technique, permitting noninvasive in vivo assessment of potential therapeutic effects, was used to measure the T2 values and tumor volumes. Animals were scanned immediately before and after PDT and 24 hours after PDT. T2 values were computed and analyzed for the tumor regions. RESULTS: For the treated tumors, the T2 values significantly increased (P<0.002) 24 hours after PDT (68.2+/- 8.5 milliseconds), compared to the pre-PDT values (55.8+/-6.6 milliseconds). For the control tumors, there was no significant difference (P = 0.53) between the pre-PDT (52.5+/-6.1 milliseconds) and 24-hour post-PDT (54.3+/-6.4 milliseconds) values. Histologic analysis showed that PDT-treated tumors demonstrated necrosis and inflammation that was not seen in the control. DISCUSSION: Changes in tumor T2 values measured by multi-slice multi-echo MR imaging provide an assay that could be useful for clinical monitoring of photodynamic therapy of prostate tumors.
AD - Department of Radiology, Case Western Reserve University & University Hospitals Case Medical Center, Cleveland, Ohio, 44106, USA. Baowei.Fei@case.edu
AN - 17960753
AU - Fei, B.
AU - Wang, H.
AU - Meyers, J. D.
AU - Feyes, D. K.
AU - Oleinick, N. L.
AU - Duerk, J. L.
C2 - 2719260
DA - Oct
DO - 10.1002/lsm.20576 [doi]
DP - Nlm
ET - 2007/10/27
KW - Animals
Humans
Image Processing, Computer-Assisted
Indoles/ therapeutic use
Magnetic Resonance Imaging/ methods
Male
Mice
Mice, Nude
Photochemotherapy
Photosensitizing Agents/ therapeutic use
Prostatic Neoplasms/ drug therapy
Transplantation, Heterologous
L1 - internal-pdf://4035643895/Fei-2007-High-field magnetic resonance imaging.pdf
LA - eng
M1 - 9
N1 - Fei, Baowei
Wang, Hesheng
Meyers, Joseph D
Feyes, Denise K
Oleinick, Nancy L
Duerk, Jeffrey L
R01CA083917/CA/NCI NIH HHS/United States
R21 CA120536/CA/NCI NIH HHS/United States
R21 CA120536-01/CA/NCI NIH HHS/United States
R21 CA120536-02/CA/NCI NIH HHS/United States
R21CA120536/CA/NCI NIH HHS/United States
R24CA110943/CA/NCI NIH HHS/United States
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
United States
Lasers in surgery and medicine
Nihms113521
Lasers Surg Med. 2007 Oct;39(9):723-30.
PY - 2007
SN - 0196-8092 (Print)
0196-8092 (Linking)
SP - 723-30
ST - High-field magnetic resonance imaging of the response of human prostate cancer to Pc 4-based photodynamic therapy in an animal model
T2 - Lasers Surg Med
TI - High-field magnetic resonance imaging of the response of human prostate cancer to Pc 4-based photodynamic therapy in an animal model
UR - http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2719260/pdf/nihms-113521.pdf
VL - 39
ID - 296
ER -
TY - JOUR
AB - The physiologic variability of blood flow to the prostate has not been studied until this time. We report the vasoactive effects of sildenafil and phenylephrine on blood flow of the normal prostate. Sildenafil increases prostate blood flow by approximately 75% and phenylephrine reduces the flow incrementally. Administration of these drugs with dynamic contrast-enhanced magnetic resonance imaging may improve the diagnosis of cancerous tissue because according to the literature, tumor angiogenic vessels lack the vasoactive physiologic response of the normal tissue.
AD - Department of Radiology, University Hospitals of Cleveland, Cleveland, OH 44106, USA. Haaga@UHRAD.com
AN - 16728965
AU - Haaga, J. R.
AU - Exner, A.
AU - Fei, B.
AU - Seftel, A.
C2 - 3779690
DA - Jan-Feb
DO - 3901486 [pii]
10.1038/sj.ijir.3901486 [doi]
DP - Nlm
ET - 2006/05/27
KW - Blood Flow Velocity/drug effects
Ephedrine/pharmacology
Humans
Magnetic Resonance Imaging
Male
Middle Aged
Phosphodiesterase Inhibitors/pharmacology
Piperazines/ pharmacology
Prostate/ blood supply
Purines
Sulfones
Vasoconstrictor Agents/pharmacology
Vasodilator Agents/ pharmacology
L1 - internal-pdf://2725836578/Haaga-2007-Semiquantitative imaging measuremen.pdf
LA - eng
M1 - 1
N1 - Haaga, J R
Exner, A
Fei, B
Seftel, A
R21 CA120536/CA/NCI NIH HHS/United States
Case Reports
England
International journal of impotence research
Nihms514171
Int J Impot Res. 2007 Jan-Feb;19(1):110-3. Epub 2006 May 25.
PY - 2007
SN - 0955-9930 (Print)
0955-9930 (Linking)
SP - 110-3
ST - Semiquantitative imaging measurement of baseline and vasomodulated normal prostatic blood flow using sildenafil
T2 - Int J Impot Res
TI - Semiquantitative imaging measurement of baseline and vasomodulated normal prostatic blood flow using sildenafil
UR - http://www.nature.com/ijir/journal/v19/n1/pdf/3901486a.pdf
VL - 19
ID - 300
ER -
TY - JOUR
AB - We are investigating in vivo small animal imaging and analysis methods for the assessment of photodynamic therapy (PDT), an emerging therapeutic modality for cancer treatment. Multiple weighted MR images were acquired from tumor-bearing mice pre- and post-PDT and 24-hour after PDT. We developed an automatic image classification method to differentiate live, necrotic and intermediate tissues within the treated tumor on the MR images. We used a multiscale diffusion filter to process the MR images before classification. A multiscale fuzzy C-means (FCM) classification method was applied along the scales. The object function of the standard FCM was modified to allow multiscale classification processing where the result from a coarse scale is used to supervise the classification in the next scale. The multiscale fuzzy C-means (MFCM) method takes noise levels and partial volume effects into the classification processing. The method was validated by simulated MR images with various noise levels. For simulated data, the classification method achieved 96.0 +/- 1.1% overlap ratio. For real mouse MR images, the classification results of the treated tumors were validated by histologic images. The overlap ratios were 85.6 +/- 5.1%, 82.4 +/- 7.8% and 80.5 +/- 10.2% for the live, necrotic, and intermediate tissues, respectively. The MR imaging and the MFCM classification methods may provide a useful tool for the assessment of the tumor response to photodynamic therapy in vivo.
AD - Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, 44106.
Department of Radiation Oncology, Case Western Reserve University, Cleveland, OH, 44106.
Department of Pathology, Case Western Reserve University, Cleveland, OH, 44106.
Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, 44106 ; Department of Radiology Case Western Reserve University, Cleveland, OH, 44106.
AN - 24386526
AU - Wang, H.
AU - Feyes, D.
AU - Mulvihill, J.
AU - Oleinick, N.
AU - Maclennan, G.
AU - Fei, B.
C2 - 3877232
DA - Mar 8
DO - 10.1117/12.710188 [doi]
DP - Nlm
ET - 2007/03/08
LA - Eng
N1 - Wang, Hesheng
Feyes, Denise
Mulvihill, John
Oleinick, Nancy
Maclennan, Gregory
Fei, Baowei
R21 CA120536/CA/NCI NIH HHS/United States
Proceedings of SPIE
Nihms432055
Proc SPIE. 2007 Mar 8;6512. doi: 10.1117/12.710188.
PY - 2007
SN - 1996-756X (Print)
1996-756X (Linking)
ST - Multiscale Fuzzy C-Means Image Classification for Multiple Weighted MR Images for the Assessment of Photodynamic Therapy in Mice
T2 - Proc SPIE
TI - Multiscale Fuzzy C-Means Image Classification for Multiple Weighted MR Images for the Assessment of Photodynamic Therapy in Mice
UR - http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=1336682
VL - 6512
ID - 298
ER -
TY - JOUR
AB - Small animals are widely used in biomedical research studies. They have compact anatomy and small organs. Therefore it is difficult to perceive tumors or cells and perform biopsies manually. Robotics technology offers a convenient and reliable solution for accurate needle insertion. In this paper, a novel 5 degrees of freedom (DOF) robot design for inserting needles into small animal subjects is proposed. The design has a compact size, is light weight, and has high resolution. Parallel mechanisms are used in the design for stable and reliable operation. The proposed robot has two gimbal joints that carry the needle mechanism. The robot can realize dexterous alignment of the needle before insertion.
AD - Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, Ohio, 44106, USA. oxb6@case.edu
AN - 19163987
AU - Bebek, O.
AU - Hwang, M. J.
AU - Fei, B.
AU - Cavusoglu, M.
C2 - 2796956
DO - 10.1109/IEMBS.2008.4650484 [doi]
DP - Nlm
ET - 2009/01/24
KW - Biopsy/ instrumentation/methods/ veterinary
Equipment Design
Equipment Failure Analysis
Needles/ veterinary
Reproducibility of Results
Robotics/ instrumentation/methods
Sensitivity and Specificity
Surgery, Computer-Assisted/ instrumentation/methods
L1 - internal-pdf://3778862615/Bebek-2008-Design of a small animal biopsy rob.pdf
LA - eng
N1 - Bebek, Ozkan
Hwang, Myun Joong
Fei, Baowei
Cavusoglu, M
R21 CA120536/CA/NCI NIH HHS/United States
R21 CA120536-01/CA/NCI NIH HHS/United States
R21 CA120536-02/CA/NCI NIH HHS/United States
Evaluation Studies
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.
United States
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference
Nihms113528
Conf Proc IEEE Eng Med Biol Soc. 2008;2008:5601-4. doi: 10.1109/IEMBS.2008.4650484.
PY - 2008
SN - 1557-170X (Print)
1557-170X (Linking)
SP - 5601-4
ST - Design of a small animal biopsy robot
T2 - Conf Proc IEEE Eng Med Biol Soc
TI - Design of a small animal biopsy robot
UR - http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2796956/pdf/nihms113528.pdf
VL - 2008
ID - 293
ER -
TY - JOUR
AB - Recent technological improvements have led to increasing clinical use of interface pressure mapping for seating pressure evaluation, which often requires repeated assessments. However, clinical conditions cannot be controlled as closely as research settings, thereby creating challenges to statistical analysis of data. A multistage longitudinal analysis and self-registration (LASR) technique is introduced that emphasizes real-time interface pressure image analysis in three dimensions. Suitable for use in clinical settings, LASR is composed of several modern statistical components, including a segmentation method. The robustness of our segmentation method is also shown. Application of LASR to analysis of data from neuromuscular electrical stimulation (NMES) experiments confirms that NMES improves static seating pressure distributions in the sacral-ischial region over time. Dynamic NMES also improves weight-shifting over time. These changes may reduce the risk of pressure ulcer development.
AD - Cleveland Advanced Platform Technology Center, Louis Stokes Cleveland VA Medical Center, Cleveland, OH 44106, USA. kmb3@case.edu
AN - 18712638
AU - Bogie, K.
AU - Wang, X.
AU - Fei, B.
AU - Sun, J.
C2 - 2729147
DP - Nlm
ET - 2008/08/21
KW - Algorithms
Buttocks/blood supply
Electric Stimulation
Electric Stimulation Therapy
Humans
Imaging, Three-Dimensional
Longitudinal Studies
Pressure
Pressure Ulcer/ prevention & control
Risk Factors
Time Factors
Wheelchairs
L1 - internal-pdf://1947648137/Bogie-2008-New technique for real-time interfa.pdf
LA - eng
M1 - 4
N1 - Bogie, Kath
Wang, Xiaofeng
Fei, Baowei
Sun, Jiayang
R21 CA120536/CA/NCI NIH HHS/United States
R21 CA120536-01/CA/NCI NIH HHS/United States
R21 CA120536-02/CA/NCI NIH HHS/United States
R21CA120536/CA/NCI NIH HHS/United States
Research Support, N.I.H., Extramural
Research Support, U.S. Gov't, Non-P.H.S.
United States
Journal of rehabilitation research and development
Nihms113522
J Rehabil Res Dev. 2008;45(4):523-35, 10 p following 535.
PY - 2008
SN - 1938-1352 (Electronic)
0748-7711 (Linking)
SP - 523-35, 10 p following 535
ST - New technique for real-time interface pressure analysis: getting more out of large image data sets
T2 - J Rehabil Res Dev
TI - New technique for real-time interface pressure analysis: getting more out of large image data sets
VL - 45
ID - 294
ER -
TY - JOUR
AB - At our institution, we are using dual-energy digital radiography (DEDR) as a cost-effective screening tool for the detection of cardiac calcification. We are evaluating DEDR using CT as the gold standard. We are developing image projection methods for the generation of digitally reconstructed radiography (DRR) from CT image volumes. Traditional visualization methods include maximum intensity projection (MIP) and average-based projection (AVG) that have difficulty to show cardiac calcification. Furthermore, MIP can over estimate the calcified lesion as it displays the maximum intensity along the projection rays regardless of tissue types. For AVG projection, the calcified tissue is usually overlapped with bone, lung and mediastinum. In order to improve the visualization of calcification on DRR images, we developed a Gaussian-weighted projection method for this particular application. We assume that the CT intensity values of calcified tissues have a Gaussian distribution. We then use multiple Gaussian functions to fit the intensity histogram. Based on the mean and standard deviation parameters, we incorporate a Gaussian weighted function into the perspective projection and display the calcification exclusively. Our digital and physical phantom studies show that the new projection method can display tissues selectively. In addition, clinical images show that the Gaussian-weighted projection method better visualizes cardiac calcification than either the AVG or MIP method and can be used to evaluate DEDR as a screening tool for the detection of coronary artery diseases.
AD - Case Western Reserve University and Xi'an Jiaotong University.
Case Western Reserve University.
University Hospitals Case Medical Center.
AN - 24386529
AU - Chen, X.
AU - Li, K.
AU - Gilkeson, R.
AU - Fei, B.
C2 - 3877249
DA - Mar 15
DO - 10.1117/12.772597 [doi]
DP - Nlm
ET - 2008/03/15
LA - Eng
N1 - Chen, Xiang
Li, Ke
Gilkeson, Robert
Fei, Baowei
R21 CA120536/CA/NCI NIH HHS/United States
Proceedings of SPIE
Nihms432049
Proc SPIE. 2008 Mar 15;6918. doi: 10.1117/12.772597.
PY - 2008
SN - 1996-756X (Print)
1996-756X (Linking)
ST - Gaussian Weighted Projection for Visualization of Cardiac Calcification
T2 - Proc SPIE
TI - Gaussian Weighted Projection for Visualization of Cardiac Calcification
UR - http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=829872
VL - 6918
ID - 291
ER -
TY - JOUR
AB - A highly efficient drug vector for photodynamic therapy (PDT) drug delivery was developed by synthesizing PEGylated gold nanoparticle conjugates, which act as a water-soluble and biocompatible "cage" that allows delivery of a hydrophobic drug to its site of PDT action. The dynamics of drug release in vitro in a two-phase solution system and in vivo in cancer-bearing mice indicates that the process of drug delivery is highly efficient, and passive targeting prefers the tumor site. With the Au NP-Pc 4 conjugates, the drug delivery time required for PDT has been greatly reduced to less than 2 h, compared to 2 days for the free drug.
AD - Center for Chemical Dynamics and Nanomaterials Research, Department of Chemistry, Case Western Reserve University, Cleveland, Ohio 44106, USA.
AN - 18642918
AU - Cheng, Y.
AU - A, C. Samia
AU - Meyers, J. D.
AU - Panagopoulos, I.
AU - Fei, B.
AU - Burda, C.
C2 - 2719258
DA - Aug 13
DO - 10.1021/ja801631c [doi]
DP - Nlm
ET - 2008/07/23
KW - Animals
Drug Delivery Systems
Gold/ chemistry
Indoles/ administration & dosage/chemistry
Metal Nanoparticles/ chemistry
Mice
Mice, Nude
Neoplasms/ drug therapy
Photochemotherapy
Polyethylene Glycols/chemistry
Radiation-Sensitizing Agents/ administration & dosage/chemistry
Singlet Oxygen/analysis
Spectrometry, Fluorescence
Spectrophotometry, Ultraviolet
L1 - internal-pdf://3012479514/Cheng-2008-Highly efficient drug delivery with.pdf
LA - eng
M1 - 32
N1 - Cheng, Yu
C Samia, Anna
Meyers, Joseph D
Panagopoulos, Irene
Fei, Baowei
Burda, Clemens
CA120536/CA/NCI NIH HHS/United States
R21 CA120536/CA/NCI NIH HHS/United States
R21 CA120536-01/CA/NCI NIH HHS/United States
R21 CA120536-02/CA/NCI NIH HHS/United States
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.
United States
Journal of the American Chemical Society
Nihms113517
J Am Chem Soc. 2008 Aug 13;130(32):10643-7. doi: 10.1021/ja801631c. Epub 2008 Jul 22.
PY - 2008
SN - 1520-5126 (Electronic)
0002-7863 (Linking)
SP - 10643-7
ST - Highly efficient drug delivery with gold nanoparticle vectors for in vivo photodynamic therapy of cancer
T2 - J Am Chem Soc
TI - Highly efficient drug delivery with gold nanoparticle vectors for in vivo photodynamic therapy of cancer
UR - http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2719258/pdf/nihms-113517.pdf
VL - 130
ID - 290
ER -
TY - JOUR
AB - We developed a new minimal path segmentation method for mouse kidney MR images. We used dynamic programming and a minimal path segmentation approach to detect the optimal path within a weighted graph between two end points. The energy function combines distance and gradient information to guide the marching curve and thus to evaluate the best path and to span a broken edge. An algorithm was developed to automatically place initial end points. Dynamic programming was used to automatically optimize and update end points during the searching procedure. Principle component analysis (PCA) was used to generate a deformable model, which serves as the prior knowledge for the selection of initial end points and for the evaluation of the best path. The method has been tested for kidney MR images acquired from 44 mice. To quantitatively assess the automatic segmentation method, we compared the results with manual segmentation. The mean and standard deviation of the overlap ratios are 95.19%+/-0.03%. The distance error between the automatic and manual segmentation is 0.82+/-0.41 pixel. The automatic minimal path segmentation method is fast, accurate, and robust and it can be applied not only for kidney images but also for other organs.
AD - Case Western Reserve University and the University of Electronic Science and Technology of China.
Case Western Reserve University, Cleveland, OH.
AN - 24386528
AU - Li, K.
AU - Fei, B.
C2 - 3877234
DA - Mar 13
DO - 10.1117/12.772347 [doi]
DP - Nlm
ET - 2008/03/13
LA - Eng
N1 - Li, Ke
Fei, Baowei
R21 CA120536/CA/NCI NIH HHS/United States
Proceedings of SPIE
Nihms432048
Proc SPIE. 2008 Mar 13;6914. doi: 10.1117/12.772347.
PY - 2008
SN - 1996-756X (Print)
1996-756X (Linking)
ST - A Deformable Model-based Minimal Path Segmentation Method for Kidney MR Images
T2 - Proc SPIE
TI - A Deformable Model-based Minimal Path Segmentation Method for Kidney MR Images
UR - http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=1329376
VL - 6914
ID - 292
ER -
TY - JOUR
AB - We are developing and evaluating choline molecular imaging with positron emission tomography (PET) for monitoring tumor response to photodynamic therapy (PDT) in animal models. Human prostate cancer (PC-3) was studied in athymic nude mice. A second-generation photosensitizer Pc 4 was used for PDT in tumor-bearing mice. MicroPET images with (11)C-choline were acquired before PDT and 48 h after PDT. Time-activity curves of (11)C-choline uptake were analyzed before and after PDT. For treated tumors, normalized choline uptake decreased significantly 48 h after PDT, compared to the same tumors pre-PDT (p < 0.001). However, for the control tumors, normalized choline uptake increased significantly (p < 0.001). PET imaging with (11)C-choline is sensitive to detect early tumor response to PDT in the animal model of human prostate cancer.
AD - Department of Radiology, Emory University, Atlanta, GA ; Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio.
AN - 23336060
AU - Fei, B.
AU - Wang, H.
AU - Wu, C.
AU - Meyers, J.
AU - Xue, L. Y.
AU - Maclennan, G.
AU - Schluchter, M.
C2 - 3546344
DO - 10.1117/12.812129 [doi]
DP - Nlm
ET - 2009/01/01
L1 - internal-pdf://4289966397/Fei-2009-Choline Molecular Imaging with Small-.pdf
LA - Eng
N1 - Fei, Baowei
Wang, Hesheng
Wu, Chunying
Meyers, Joseph
Xue, Liang-Yan
Maclennan, Gregory
Schluchter, Mark
R21 CA120536/CA/NCI NIH HHS/United States
Proceedings of SPIE
Nihms432050
Proc SPIE. 2009;7262:726211. Epub 2009 Feb 27.
PY - 2009
SN - 1996-756X (Print)
1996-756X (Linking)
SP - 726211
ST - Choline Molecular Imaging with Small-animal PET for Monitoring Tumor Cellular Response to Photodynamic Therapy of Cancer
T2 - Proc SPIE
TI - Choline Molecular Imaging with Small-animal PET for Monitoring Tumor Cellular Response to Photodynamic Therapy of Cancer
UR - http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3546344/pdf/nihms432050.pdf
VL - 7262
ID - 289
ER -
TY - JOUR
AB - We are developing MRI-based attenuation correction methods for PET images. PET has high sensitivity but relatively low resolution and little anatomic details. MRI can provide excellent anatomical structures with high resolution and high soft tissue contrast. MRI can be used to delineate tumor boundaries and to provide an anatomic reference for PET, thereby improving quantitation of PET data. Combined PET/MRI can offer metabolic, functional and anatomic information and thus can provide a powerful tool to study the mechanism of a variety of diseases. Accurate attenuation correction represents an essential component for the reconstruction of artifact-free, quantitative PET images. Unfortunately, the present design of hybrid PET/MRI does not offer measured attenuation correction using a transmission scan. This problem may be solved by deriving attenuation maps from corresponding anatomic MR images. Our approach combines image registration, classification, and attenuation correction in a single scheme. MR images and the preliminary reconstruction of PET data are first registered using our automatic registration method. MRI images are then classified into different tissue types using our multiscale fuzzy C-mean classification method. The voxels of classified tissue types are assigned theoretical tissue-dependent attenuation coefficients to generate attenuation correction factors. Corrected PET emission data are then reconstructed using a three-dimensional filtered back projection method and an order subset expectation maximization method. Results from simulated images and phantom data demonstrated that our attenuation correction method can improve PET data quantitation and it can be particularly useful for combined PET/MRI applications.
AD - Departments of Radiology, Emory University, Atlanta, GA. Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio.
AN - 23682307
AU - Fei, B.
AU - Yang, X.
AU - Wang, H.
C2 - 3653447
DA - Feb 27
DO - 10.1117/12.813755 [doi]
DP - Nlm
ET - 2009/02/27
LA - Eng
N1 - Fei, Baowei
Yang, Xiaofeng
Wang, Hesheng
R21 CA120536/CA/NCI NIH HHS/United States
Proceedings of SPIE
Nihms432051
Proc SPIE. 2009 Feb 27;7262. pii: 726208.
PY - 2009
SN - 1996-756X (Print)
1996-756X (Linking)
ST - An MRI-based Attenuation Correction Method for Combined PET/MRI Applications
T2 - Proc SPIE
TI - An MRI-based Attenuation Correction Method for Combined PET/MRI Applications
UR - http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=815881
VL - 7262
ID - 288
ER -
TY - JOUR
AB - We are developing a minimal path searching method for active shape model (ASM)-based segmentation for detection of lung boundaries on digital radiographs. With the conventional ASM method, the position and shape parameters of the model points are iteratively refined and the target points are updated by the least Mahalanobis distance criterion. We propose an improved searching strategy that extends the searching points in a fan-shape region instead of along the normal direction. A minimal path (MP) deformable model is applied to drive the searching procedure. A statistical shape prior model is incorporated into the segmentation. In order to keep the smoothness of the shape, a smooth constraint is employed to the deformable model. To quantitatively assess the ASM-MP segmentation, we compare the automatic segmentation with manual segmentation for 72 lung digitized radiographs. The distance error between the ASM-MP and manual segmentation is 1.75 +/- 0.33 pixels, while the error is 1.99 +/- 0.45 pixels for the ASM. Our results demonstrate that our ASM-MP method can accurately segment the lung on digital radiographs.
AD - Quantitative BioImaging Laboratory, Department of Radiology, Emory University, Atlanta, GA 30322.
AN - 24386531
AU - Guo, S.
AU - Fei, B.
C2 - 3877238
DA - Mar 27
DO - 10.1117/12.812575 [doi]
DP - Nlm
ET - 2009/03/27
LA - Eng
N1 - Guo, Shengwen
Fei, Baowei
R21 CA120536/CA/NCI NIH HHS/United States
Proceedings of SPIE
Nihms432053
Proc SPIE. 2009 Mar 27;7259. doi: 10.1117/12.812575.
PY - 2009
SN - 1996-756X (Print)
1996-756X (Linking)
ST - A Minimal Path Searching Approach for Active Shape Model (ASM)-based Segmentation of the Lung
T2 - Proc SPIE
TI - A Minimal Path Searching Approach for Active Shape Model (ASM)-based Segmentation of the Lung
UR - http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=1335511
VL - 7259
ID - 286
ER -
TY - JOUR
AB - A fully automatic, multiscale fuzzy C-means (MsFCM) classification method for MR images is presented in this paper. We use a diffusion filter to process MR images and to construct a multiscale image series. A multiscale fuzzy C-means classification method is applied along the scales from the coarse to fine levels. The objective function of the conventional fuzzy C-means (FCM) method is modified to allow multiscale classification processing where the result from a coarse scale supervises the classification in the next fine scale. The method is robust for noise and low-contrast MR images because of its multiscale diffusion filtering scheme. The new method was compared with the conventional FCM method and a modified FCM (MFCM) method. Validation studies were performed on synthesized images with various contrasts and on the McGill brain MR image database. Our MsFCM method consistently performed better than the conventional FCM and MFCM methods. The MsFCM method achieved an overlap ratio of greater than 90% as validated by the ground truth. Experiments results on real MR images were given to demonstrate the effectiveness of the proposed method. Our multiscale fuzzy C-means classification method is accurate and robust for various MR images. It can provide a quantitative tool for neuroimaging and other applications.
AD - Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH 44106, USA.
AN - 18684658
AU - Wang, H.
AU - Fei, B.
C2 - 2817958
DA - Apr
DO - S1361-8415(08)00071-6 [pii]
10.1016/j.media.2008.06.014 [doi]
DP - Nlm
ET - 2008/08/08
KW - Algorithms
Artificial Intelligence
Brain/ anatomy & histology
Cluster Analysis
Diffusion Magnetic Resonance Imaging/instrumentation/ methods
Fuzzy Logic
Humans
Image Enhancement/ methods
Image Interpretation, Computer-Assisted/ methods
Pattern Recognition, Automated/ methods
Phantoms, Imaging
Reproducibility of Results
Sensitivity and Specificity
Signal Processing, Computer-Assisted
L1 - internal-pdf://1399293558/Wang-2009-A modified fuzzy C-means classificat.pdf
LA - eng
M1 - 2
N1 - Wang, Hesheng
Fei, Baowei
R21 CA120536/CA/NCI NIH HHS/United States
R21 CA120536-01/CA/NCI NIH HHS/United States
R21 CA120536-02/CA/NCI NIH HHS/United States
R21CA120536/CA/NCI NIH HHS/United States
R24CA110943/CA/NCI NIH HHS/United States
Evaluation Studies
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Netherlands
Medical image analysis
Nihms108085
Med Image Anal. 2009 Apr;13(2):193-202. doi: 10.1016/j.media.2008.06.014. Epub 2008 Jul 5.
PY - 2009
SN - 1361-8423 (Electronic)
1361-8415 (Linking)
SP - 193-202
ST - A modified fuzzy C-means classification method using a multiscale diffusion filtering scheme
T2 - Med Image Anal
TI - A modified fuzzy C-means classification method using a multiscale diffusion filtering scheme
UR - http://ac.els-cdn.com/S1361841508000716/1-s2.0-S1361841508000716-main.pdf?_tid=2afc2ccc-c133-11e4-a721-00000aab0f27&acdnat=1425338803_1261da35e2cadec8f458c202f50d408a
VL - 13
ID - 285
ER -
TY - JOUR
AB - Accurate quantification of positron emission tomography (PET) is important for diagnosis and assessment of cancer treatment. The low spatial resolution of PET imaging induces partial volume effect to PET images that biases quantification. A PET partial volume correction method is proposed using high-resolution, anatomical information from magnetic resonance images (MRI). The corrected PET is pursued by removing the convolution of PET point spread function (PSF) and by preserving edges present in PET and the aligned MR images. The correction is implemented in a Bayesian's deconvolution framework that is minimized by a conjugate gradient method. The method is evaluated on simulated phantom and brain PET images. The results show that the method effectively restores 102 +/- 7% of the true PET activity with a size of greater than the full-width at half maximum of the point spread function. We also applied the method to synthesized brain PET data. The method does not require prior information about tracer activity within tissue regions. It can offer a partial volume correction method for various PET applications and can be particularly useful for combined PET/MRI studies.
AD - Department of Biomedical Engineering, Case Western Reserve University, Atlanta, GA ; Department of Radiology and Imaging Sciences, Emory University School of Medicine, 1841 Clifton Rd NE, Atlanta, GA 30329.
Department of Radiology and Imaging Sciences, Emory University School of Medicine, 1841 Clifton Rd NE, Atlanta, GA 30329. ; Department of Biomedical Engineering, Case Western Reserve University, Atlanta, GA.
AN - 24386530
AU - Wang, H.
AU - Fei, B.
C2 - 3877222
DA - Mar 27
DO - 10.1117/12.812474 [doi]
DP - Nlm
ET - 2009/03/27
LA - Eng
N1 - Wang, Hesheng
Fei, Baowei
R21 CA120536/CA/NCI NIH HHS/United States
Proceedings of SPIE
Nihms432052
Proc SPIE. 2009 Mar 27;7259. doi: 10.1117/12.812474.
PY - 2009
SN - 1996-756X (Print)
1996-756X (Linking)
ST - An MRI-guided PET Partial Volume Correction Method
T2 - Proc SPIE
TI - An MRI-guided PET Partial Volume Correction Method
UR - http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=1335548
VL - 7259
ID - 287
ER -
TY - JOUR
AB - Photodynamic therapy (PDT) is a relatively new therapy that has shown promise for treating various cancers in both preclinical and clinical studies. The present study evaluated the potential use of PET with radiolabeled choline to monitor early tumor response to PDT in animal models. METHODS: Two human prostate cancer models (PC-3 and CWR22) were studied in athymic nude mice. A second-generation photosensitizer, phthalocyanine 4 (Pc 4), was delivered to each animal by a tail vein injection 48 h before laser illumination. Small-animal PET images with (11)C-choline were acquired before PDT and at 1, 24, and 48 h after PDT. Time-activity curves of (11)C-choline uptake were analyzed before and after PDT. The percentage of the injected dose per gram of tissue was quantified for both treated and control tumors at each time point. In addition, Pc 4-PDT was performed in cell cultures. Cell viability and (11)C-choline uptake in PDT-treated and control cells were measured. RESULTS: For treated tumors, normalized (11)C-choline uptake decreased significantly 24 and 48 h after PDT, compared with the same tumors before PDT (P < 0.001). For the control tumors, normalized (11)C-choline uptake increased significantly. For mice with CWR22 tumors, the prostate-specific antigen level decreased 24 and 48 h after PDT. Pc 4-PDT in cell culture showed that the treated tumor cells, compared with the control cells, had less than 50% (11)C-choline activity at 5, 30, and 45 min after PDT, whereas the cell viability test showed that the treated cells were viable longer than 7 h after PDT. CONCLUSION: PET with (11)C-choline is sensitive for detecting early changes associated with Pc 4-PDT in mouse models of human prostate cancer. Choline PET has the potential to determine whether a PDT-treated tumor responds to treatment within 48 h after therapy.
AD - Department of Radiology, Emory Center for Systems Imaging, Emory University, Atlanta, Georgia 30329, USA. bfei@emory.edu
AN - 20008981
AU - Fei, B.
AU - Wang, H.
AU - Wu, C.
AU - Chiu, S. M.
C2 - 2999358
DA - Jan
DO - jnumed.109.067579 [pii]
10.2967/jnumed.109.067579 [doi]
DP - Nlm
ET - 2009/12/17
KW - Algorithms
Animals
Cell Line, Tumor
Cell Survival/drug effects
Choline/chemical synthesis/ diagnostic use/pharmacokinetics
Humans
Image Processing, Computer-Assisted
Indoles/ therapeutic use
Isotope Labeling
Male
Mice
Mice, Nude
Neoplasm Transplantation
Neoplasms/ drug therapy/pathology/ radionuclide imaging
Photochemotherapy
Photosensitizing Agents/ therapeutic use
Positron-Emission Tomography
Prostatic Neoplasms/drug therapy/pathology/radionuclide imaging
Radiopharmaceuticals/chemical synthesis/ diagnostic use/pharmacokinetics
L1 - internal-pdf://1684774208/Fei-2010-Choline PET for monitoring early tumo.pdf
LA - eng
M1 - 1
N1 - Fei, Baowei
Wang, Hesheng
Wu, Chunying
Chiu, Song-mao
CA110943/CA/NCI NIH HHS/United States
CA120536/CA/NCI NIH HHS/United States
R21 CA120536/CA/NCI NIH HHS/United States
R21 CA120536-01/CA/NCI NIH HHS/United States
R21 CA120536-02/CA/NCI NIH HHS/United States
Research Support, N.I.H., Extramural
United States
Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Nihms255626
J Nucl Med. 2010 Jan;51(1):130-8. doi: 10.2967/jnumed.109.067579. Epub 2009 Dec 15.
PY - 2010
SN - 1535-5667 (Electronic)
0161-5505 (Linking)
SP - 130-8
ST - Choline PET for monitoring early tumor response to photodynamic therapy
T2 - J Nucl Med
TI - Choline PET for monitoring early tumor response to photodynamic therapy
UR - http://jnm.snmjournals.org/content/51/1/130.full.pdf
VL - 51
ID - 284
ER -
TY - JOUR
AB - PURPOSE: To examine diffusion-weighted MRI (DW-MRI) for assessing the early tumor response to photodynamic therapy (PDT). MATERIALS AND METHODS: Subcutaneous tumor xenografts of human prostate cancer cells (CWR22) were initiated in athymic nude mice. A second-generation photosensitizer, Pc 4, was delivered to each animal by a tail vein injection 48 h before laser illumination. A dedicated high-field (9.4 Tesla) small animal MR scanner was used to acquire diffusion-weighted MR images pre-PDT and 24 h after the treatment. DW-MRI and apparent diffusion coefficients (ADC) were analyzed for 24 treated and 5 control mice with photosensitizer only or laser light only. Tumor size, prostate specific antigen (PSA) level, and tumor histology were obtained at different time points to examine the treatment effect. RESULTS: Treated mice showed significant tumor size shrinkage and decrease of PSA level within 7 days after the treatment. The average ADC of the 24 treated tumors increased 24 h after PDT (P < 0.001) comparing with pre-PDT. The average ADC was 0.511 +/- 0.119 x 10(-3) mm(2)/s pre-PDT and 0.754 +/- 0.181 x 10(-3) mm(2)/s 24 h after the PDT. There is no significant difference in ADC values pre-PDT and 24 h after PDT in the control tumors (P = 0.20). CONCLUSION: The change of tumor ADC values measured by DW-MRI may provide a noninvasive imaging marker for monitoring tumor response to Pc 4-PDT as early as 24 h.
AD - Emory Center for Systems Imaging, Department of Radiology, Emory University, Atlanta, Georgia 30329, USA.
AN - 20677270
AU - Wang, H.
AU - Fei, B.
C2 - 3076282
DA - Aug
DO - 10.1002/jmri.22247 [doi]
DP - Nlm
ET - 2010/08/03
KW - Animals
Cell Line, Tumor
Diffusion
Diffusion Magnetic Resonance Imaging/ methods
Humans
Male
Mice
Mice, Nude
Neoplasm Transplantation
Photochemotherapy/ methods
Photosensitizing Agents/pharmacology
Prostatic Neoplasms/ pathology/ therapy
Treatment Outcome
Tumor Markers, Biological
L1 - internal-pdf://1178050090/Wang-2010-Diffusion-weighted MRI for monitorin.pdf
LA - eng
M1 - 2
N1 - Wang, Hesheng
Fei, Baowei
R21 CA120536/CA/NCI NIH HHS/United States
R21 CA120536-01/CA/NCI NIH HHS/United States
R21 CA120536-02/CA/NCI NIH HHS/United States
R21CA120536/CA/NCI NIH HHS/United States
R24CA110943/CA/NCI NIH HHS/United States
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
United States
Journal of magnetic resonance imaging : JMRI
Nihms255624
J Magn Reson Imaging. 2010 Aug;32(2):409-17. doi: 10.1002/jmri.22247.
PY - 2010
SN - 1522-2586 (Electronic)
1053-1807 (Linking)
SP - 409-17
ST - Diffusion-weighted MRI for monitoring tumor response to photodynamic therapy
T2 - J Magn Reson Imaging
TI - Diffusion-weighted MRI for monitoring tumor response to photodynamic therapy
UR - http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3076282/pdf/nihms255624.pdf
VL - 32
ID - 283
ER -
TY - JOUR
AB - The current definitive diagnosis of prostate cancer is transrectal ultrasound (TRUS) guided biopsy. However, the current procedure is limited by using 2D biopsy tools to target 3D biopsy locations. This paper presents a new method for automatic segmentation of the prostate in three-dimensional transrectal ultrasound images, by extracting texture features and by statistically matching geometrical shape of the prostate. A set of Wavelet-based support vector machines (W-SVMs) are located and trained at different regions of the prostate surface. The WSVMs capture texture priors of ultrasound images for classification of the prostate and non-prostate tissues in different zones around the prostate boundary. In the segmentation procedure, these W-SVMs are trained in three sagittal, coronal, and transverse planes. The pre-trained W-SVMs are employed to tentatively label each voxel around the surface of the model as a prostate or non-prostate voxel by the texture matching. The labeled voxels in three planes after post-processing is overlaid on a prostate probability model. The probability prostate model is created using 10 segmented prostate data. Consequently, each voxel has four labels: sagittal, coronal, and transverse planes and one probability label. By defining a weight function for each labeling in each region, each voxel is labeled as a prostate or non-prostate voxel. Experimental results by using real patient data show the good performance of the proposed model in segmenting the prostate from ultrasound images.
AD - Department of Radiology, Emory University, 1841 Clifton Rd, NE, Atlanta, GA, USA 30329.
AN - 22468205
AU - Akbari, H.
AU - Yang, X.
AU - Halig, L. V.
AU - Fei, B.
C2 - 3314427
DO - 10.1117/12.878072 [doi]
DP - Nlm
ET - 2011/01/01
L1 - internal-pdf://0047872161/Akbari-2011-3D Segmentation of Prostate Ultras.pdf
LA - Eng
N1 - Akbari, Hamed
Yang, Xiaofeng
Halig, Luma V
Fei, Baowei
R01 CA156775/CA/NCI NIH HHS/United States
R01 CA156775-01/CA/NCI NIH HHS/United States
R01 CA156775-02/CA/NCI NIH HHS/United States
R01 CA156775-03/CA/NCI NIH HHS/United States
Proceedings of SPIE
Nihms362788
Proc SPIE. 2011;7962:79622K. Epub 2011 Mar 14.
PY - 2011
SN - 1996-756X (Print)
1996-756X (Linking)
SP - 79622K
ST - 3D Segmentation of Prostate Ultrasound images Using Wavelet Transform
T2 - Proc SPIE
TI - 3D Segmentation of Prostate Ultrasound images Using Wavelet Transform
UR - http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3314427/pdf/nihms362788.pdf
VL - 7962
ID - 282
ER -
TY - JOUR
AB - We present a 3D non-rigid registration algorithm for the potential use in combining PET/CT and transrectal ultrasound (TRUS) images for targeted prostate biopsy. Our registration is a hybrid approach that simultaneously optimizes the similarities from point-based registration and volume matching methods. The 3D registration is obtained by minimizing the distances of corresponding points at the surface and within the prostate and by maximizing the overlap ratio of the bladder neck on both images. The hybrid approach not only capture deformation at the prostate surface and internal landmarks but also the deformation at the bladder neck regions. The registration uses a soft assignment and deterministic annealing process. The correspondences are iteratively established in a fuzzy-to-deterministic approach. B-splines are used to generate a smooth non-rigid spatial transformation. In this study, we tested our registration with pre- and post-biopsy TRUS images of the same patients. Registration accuracy is evaluated using manual defined anatomic landmarks, i.e. calcification. The root-mean-squared (RMS) of the difference image between the reference and floating images was decreased by 62.6+/-9.1% after registration. The mean target registration error (TRE) was 0.88+/-0.16 mm, i.e. less than 3 voxels with a voxel size of 0.38x0.38x0.38 mm3 for all five patients. The experimental results demonstrate the robustness and accuracy of the 3D non-rigid registration algorithm.
AD - Department of Radiology, Emory University.
AN - 24027609
AU - Yang, X.
AU - Akbari, H.
AU - Halig, L.
AU - Fei, B.
C2 - 3766999
DA - Mar 1
DO - 10.1117/12.878153 [doi]
DP - Nlm
ET - 2011/03/01
L1 - internal-pdf://0969219993/Yang-2011-3D Non-rigid Registration Using Surf.pdf
LA - Eng
N1 - Yang, Xiaofeng
Akbari, Hamed
Halig, Luma
Fei, Baowei
R01 CA156775/CA/NCI NIH HHS/United States
R01 CA156775-01/CA/NCI NIH HHS/United States
R01 CA156775-02/CA/NCI NIH HHS/United States
R01 CA156775-03/CA/NCI NIH HHS/United States
Proceedings of SPIE
Nihms362780
Proc SPIE. 2011 Mar 1;7964:79642V.
PY - 2011
SN - 1996-756X (Print)
1996-756X (Linking)
SP - 79642V
ST - 3D Non-rigid Registration Using Surface and Local Salient Features for Transrectal Ultrasound Image-guided Prostate Biopsy
T2 - Proc SPIE
TI - 3D Non-rigid Registration Using Surface and Local Salient Features for Transrectal Ultrasound Image-guided Prostate Biopsy
UR - http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3766999/pdf/nihms362780.pdf
VL - 7964
ID - 278
ER -
TY - JOUR
AB - PURPOSE: Classification of magnetic resonance (MR) images has many clinical and research applications. Because of multiple factors such as noise, intensity inhomogeneity, and partial volume effects, MR image classification can be challenging. Noise in MRI can cause the classified regions to become disconnected. Partial volume effects make the assignment of a single class to one region difficult. Because of intensity inhomogeneity, the intensity of the same tissue can vary with respect to the location of the tissue within the same image. The conventional "hard" classification method restricts each pixel exclusively to one class and often results in crisp results. Fuzzy C-mean (FCM) classification or "soft" segmentation has been extensively applied to MR images, in which pixels are partially classified into multiple classes using varying memberships to the classes. Standard FCM, however, is sensitive to noise and cannot effectively compensate for intensity inhomogeneities. This paper presents a method to obtain accurate MR brain classification using a modified multiscale and multiblock FCM. METHODS: An automatic, multiscale and multiblock fuzzy C-means (MsbFCM) classification method with MR intensity correction is presented in this paper. We use a bilateral filter to process MR images and to build a multiscale image series by increasing the standard deviation of spatial function and by reducing the standard deviation of range function. At each scale, we separate the image into multiple blocks and for every block a multiscale fuzzy C-means classification method is applied along the scales from the coarse to fine levels in order to overcome the effect of intensity inhomogeneity. The result from a coarse scale supervises the classification in the next fine scale. The classification method is tested with noisy MR images with intensity inhomogeneity. RESULTS: Our method was compared with the conventional FCM, a modified FCM (MFCM) and multiscale FCM (MsFCM) method. Validation studies were performed on synthesized images with various contrasts, on the simulated brain MR database, and on real MR images. Our MsbFCM method consistently performed better than the conventional FCM, MFCM, and MsFCM methods. The MsbFCM method achieved an overlap ratio of 91% or higher. Experimental results using real MR images demonstrate the effectiveness of the proposed method. Our MsbFCM classification method is accurate and robust for various MR images. CONCLUSIONS: As our classification method did not assume a Gaussian distribution of tissue intensity, it could be used on other image data for tissue classification and quantification. The automatic classification method can provide a useful quantification tool in neuroimaging and other applications.
AD - Department of Radiology and Imaging Sciences, Emory University, Atlanta, Georgia 30329, USA.
AN - 21815363
AU - Yang, X.
AU - Fei, B.
C2 - 3117893
DA - Jun
DP - Nlm
ET - 2011/08/06
KW - Algorithms
Brain
Humans
Image Processing, Computer-Assisted/ methods
Magnetic Resonance Imaging/ methods
L1 - internal-pdf://2179874024/Yang-2011-A multiscale and multiblock fuzzy C-.pdf
LA - eng
M1 - 6
N1 - Yang, Xiaofeng
Fei, Baowei
P50CA128301/CA/NCI NIH HHS/United States
R01 CA156775/CA/NCI NIH HHS/United States
R01CA156775/CA/NCI NIH HHS/United States
UL1RR025008/RR/NCRR NIH HHS/United States
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
United States
Medical physics
Med Phys. 2011 Jun;38(6):2879-91.
PY - 2011
SN - 0094-2405 (Print)
0094-2405 (Linking)
SP - 2879-91
ST - A multiscale and multiblock fuzzy C-means classification method for brain MR images
T2 - Med Phys
TI - A multiscale and multiblock fuzzy C-means classification method for brain MR images
UR - http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3117893/pdf/MPHYA6-000038-002879_1.pdf
VL - 38
ID - 276
ER -
TY - JOUR
AB - Based on the Radon transform, a wavelet multiscale denoising method is proposed for MR images. The approach explicitly accounts for the Rician nature of MR data. Based on noise statistics we apply the Radon transform to the original MR images and use the Gaussian noise model to process the MR sinogram image. A translation invariant wavelet transform is employed to decompose the MR 'sinogram' into multiscales in order to effectively denoise the images. Based on the nature of Rician noise we estimate noise variance in different scales. For the final denoised sinogram we apply the inverse Radon transform in order to reconstruct the original MR images. Phantom, simulation brain MR images, and human brain MR images were used to validate our method. The experiment results show the superiority of the proposed scheme over the traditional methods. Our method can reduce Rician noise while preserving the key image details and features. The wavelet denoising method can have wide applications in MRI as well as other imaging modalities.
AD - Department of Biomedical Engineering, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, People's Republic of China ; Department of Radiology, Emory University, Atlanta, GA 30329, USA.
AN - 23853425
AU - Yang, X.
AU - Fei, B.
C2 - 3707516
DA - Feb 1
DO - 10.1088/0957-0233/22/2/025803 [doi]
DP - Nlm
ET - 2011/02/01
L1 - internal-pdf://0520839732/Yang-2011-A wavelet multiscale denoising algor.pdf
LA - Eng
M1 - 2
N1 - Yang, Xiaofeng
Fei, Baowei
R01 CA156775/CA/NCI NIH HHS/United States
R01 CA156775-01/CA/NCI NIH HHS/United States
R01 CA156775-02/CA/NCI NIH HHS/United States
R01 CA156775-03/CA/NCI NIH HHS/United States
Measurement science & technology
Nihms362727
Meas Sci Technol. 2011 Feb 1;22(2):25803.
PY - 2011
SN - 0957-0233 (Print)
0957-0233 (Linking)
SP - 25803
ST - A wavelet multiscale denoising algorithm for magnetic resonance (MR) images
T2 - Meas Sci Technol
TI - A wavelet multiscale denoising algorithm for magnetic resonance (MR) images
UR - http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3707516/pdf/nihms362727.pdf
VL - 22
ID - 279
ER -
TY - JOUR
AB - A fully automatic, multiscale and multiblock fuzzy C-means (MsbFCM) classification method with intensity correction for MR images is presented in this paper. We use a bilateral filter to process MR images and to build a multiscale image series by increasing the standard deviation of spatial function and reducing the standard deviation of range function. We separate every scale image into multiple blocks and for every block a multiscale fuzzy C-means classification method is applied along the scales from the coarse to fine levels to overcome the effect of intensity inhomogeneity. The method is robust for noise MR images with intensity inhomogeneity because of its multiscale and multiblock bilateral filtering scheme. Our method was compared with the conventional FCM, a modified FCM (MFCM) and multiscale FCM (MsFCM) method on synthesized images, simulated brain MR images, and real MR images. The MsbFCM method achieved an overlap ratio of greater than 91% as validated by the ground truth even if original images have 9% noise and 40% intensity inhomogeneity. Experimental results using real MR images demonstrate the effectiveness of the proposed method. Our MsbFCM classification method is accurate and robust for various MR images.
AD - Department of Radiology, Emory University, Atlanta, GA 30329.
AN - 23358117
AU - Yang, X.
AU - Fei, B.
C2 - 3552386
DP - Nlm
ET - 2011/01/01
LA - Eng
N1 - Yang, Xiaofeng
Fei, Baowei
R01 CA156775/CA/NCI NIH HHS/United States
R01 CA156775-01/CA/NCI NIH HHS/United States
R01 CA156775-02/CA/NCI NIH HHS/United States
R01 CA156775-03/CA/NCI NIH HHS/United States
International Conference on Bioinformatics and Biomedical Engineering : [proceedings]. International Conference on Bioinformatics and Biomedical Engineering
Nihms432047
Int Conf Bioinform Biomed Eng. 2011:1-4.
PY - 2011
SN - 2151-7614 (Print)
2151-7614 (Linking)
SP - 1-4
ST - A MR Brain Classification Method Based on Multiscale and Multiblock Fuzzy C-means
T2 - Int Conf Bioinform Biomed Eng
TI - A MR Brain Classification Method Based on Multiscale and Multiblock Fuzzy C-means
ID - 280
ER -
TY - JOUR
AB - We are developing a molecular image-directed, 3D ultrasound-guided, targeted biopsy system for improved detection of prostate cancer. In this paper, we propose an automatic 3D segmentation method for transrectal ultrasound (TRUS) images, which is based on multi-atlas registration and statistical texture prior. The atlas database includes registered TRUS images from previous patients and their segmented prostate surfaces. Three orthogonal Gabor filter banks are used to extract texture features from each image in the database. Patient-specific Gabor features from the atlas database are used to train kernel support vector machines (KSVMs) and then to segment the prostate image from a new patient. The segmentation method was tested in TRUS data from 5 patients. The average surface distance between our method and manual segmentation is 1.61 +/- 0.35 mm, indicating that the atlas-based automatic segmentation method works well and could be used for 3D ultrasound-guided prostate biopsy.
AD - Department of Radiology, Emory University, Atlanta, GA, USA.
AN - 22708024
AU - Yang, X.
AU - Schuster, D.
AU - Master, V.
AU - Nieh, P.
AU - Fenster, A.
AU - Fei, B.
C2 - 3375607
DO - 10.1117/12.877888 [doi]
DP - Nlm
ET - 2011/01/01
LA - Eng
N1 - Yang, Xiaofeng
Schuster, David
Master, Viraj
Nieh, Peter
Fenster, Aaron
Fei, Baowei
R01 CA156775/CA/NCI NIH HHS/United States
R01 CA156775-01/CA/NCI NIH HHS/United States
R01 CA156775-02/CA/NCI NIH HHS/United States
R01 CA156775-03/CA/NCI NIH HHS/United States
Proceedings of SPIE
Nihms362792
Proc SPIE. 2011;7964. pii: 796432. Epub 2011 Mar 1.
PY - 2011
SN - 1996-756X (Print)
1996-756X (Linking)
ST - Automatic 3D Segmentation of Ultrasound Images Using Atlas Registration and Statistical Texture Prior
T2 - Proc SPIE
TI - Automatic 3D Segmentation of Ultrasound Images Using Atlas Registration and Statistical Texture Prior
UR - http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=1349950
VL - 7964
ID - 281
ER -
TY - JOUR
AB - Breast tissue classification can provide quantitative measurements of breast composition, density and tissue distribution for diagnosis and identification of high-risk patients. In this study, we present an automatic classification method to classify high-resolution dedicated breast CT images. The breast is classified into skin, fat and glandular tissue. First, we use a multiscale bilateral filter to reduce noise and at the same time keep edges on the images. As skin and glandular tissue have similar CT values in breast CT images, we use morphologic operations to get the mask of the skin based on information of its position. Second, we use a modified fuzzy C-mean classification method twice, one for the skin and the other for the fatty and glandular tissue. We compared our classified results with manually segmentation results and used Dice overlap ratios to evaluate our classification method. We also tested our method using added noise in the images. The overlap ratios for glandular tissue were above 94. 7% for data from five patients. Evaluation results showed that our method is robust and accurate.
AD - Department of Radiology, Emory University.
AN - 24027608
AU - Yang, X.
AU - Sechopoulos, I.
AU - Fei, B.
C2 - 3766982
DA - Mar 14
DO - 10.1117/12.877881 [doi]
DP - Nlm
ET - 2011/03/14
L1 - internal-pdf://0391842638/Yang-2011-Automatic Tissue Classification for.pdf
LA - Eng
N1 - Yang, Xiaofeng
Sechopoulos, Ioannis
Fei, Baowei
R01 CA156775/CA/NCI NIH HHS/United States
R01 CA156775-01/CA/NCI NIH HHS/United States
R01 CA156775-02/CA/NCI NIH HHS/United States
R01 CA156775-03/CA/NCI NIH HHS/United States
Proceedings of SPIE
Nihms362783
Proc SPIE. 2011 Mar 14;7962:79623H.
PY - 2011
SN - 1996-756X (Print)
1996-756X (Linking)
SP - 79623H
ST - Automatic Tissue Classification for High-resolution Breast CT Images Based on Bilateral Filtering
T2 - Proc SPIE
TI - Automatic Tissue Classification for High-resolution Breast CT Images Based on Bilateral Filtering
UR - http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3766982/pdf/nihms362783.pdf
VL - 7962
ID - 277
ER -
TY - JOUR
AB - PURPOSE: Transrectal ultrasound (TRUS) imaging is clinically used in prostate biopsy and therapy. Segmentation of the prostate on TRUS images has many applications. In this study, a three-dimensional (3D) segmentation method for TRUS images of the prostate is presented for 3D ultrasound-guided biopsy. METHODS: This segmentation method utilizes a statistical shape, texture information, and intensity profiles. A set of wavelet support vector machines (W-SVMs) is applied to the images at various subregions of the prostate. The W-SVMs are trained to adaptively capture the features of the ultrasound images in order to differentiate the prostate and nonprostate tissue. This method consists of a set of wavelet transforms for extraction of prostate texture features and a kernel-based support vector machine to classify the textures. The voxels around the surface of the prostate are labeled in sagittal, coronal, and transverse planes. The weight functions are defined for each labeled voxel on each plane and on the model at each region. In the 3D segmentation procedure, the intensity profiles around the boundary between the tentatively labeled prostate and nonprostate tissue are compared to the prostate model. Consequently, the surfaces are modified based on the model intensity profiles. The segmented prostate is updated and compared to the shape model. These two steps are repeated until they converge. Manual segmentation of the prostate serves as the gold standard and a variety of methods are used to evaluate the performance of the segmentation method. RESULTS: The results from 40 TRUS image volumes of 20 patients show that the Dice overlap ratio is 90.3% +/- 2.3% and that the sensitivity is 87.7% +/- 4.9%. CONCLUSIONS: The proposed method provides a useful tool in our 3D ultrasound image-guided prostate biopsy and can also be applied to other applications in the prostate.
AD - Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA 30329, USA.
AN - 22755682
AU - Akbari, H.
AU - Fei, B.
C2 - 3360689
DA - Jun
DO - 10.1118/1.4709607 [doi]
DP - Nlm
ET - 2012/07/05
KW - Humans
Imaging, Three-Dimensional/ methods
Male
Prostate/ultrasonography
Support Vector Machines
Ultrasonography/ methods
L1 - internal-pdf://3744237626/Akbari-2012-3D ultrasound image segmentation u.pdf
LA - eng
M1 - 6
N1 - Akbari, Hamed
Fei, Baowei
P50CA128301/CA/NCI NIH HHS/United States
P50CA128613/CA/NCI NIH HHS/United States
R01 CA156775/CA/NCI NIH HHS/United States
R01CA156775/CA/NCI NIH HHS/United States
UL1 RR025008/RR/NCRR NIH HHS/United States
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, P.H.S.
United States
Medical physics
Med Phys. 2012 Jun;39(6):2972-84. doi: 10.1118/1.4709607.
PY - 2012
SN - 0094-2405 (Print)
0094-2405 (Linking)
SP - 2972-84
ST - 3D ultrasound image segmentation using wavelet support vector machines
T2 - Med Phys
TI - 3D ultrasound image segmentation using wavelet support vector machines
UR - http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3360689/pdf/MPHYA6-000039-002972_1.pdf
VL - 39
ID - 269
ER -
TY - JOUR
AB - Hyperspectral imaging (HSI) is an emerging modality for various medical applications. Its spectroscopic data might be able to be used to noninvasively detect cancer. Quantitative analysis is often necessary in order to differentiate healthy from diseased tissue. We propose the use of an advanced image processing and classification method in order to analyze hyperspectral image data for prostate cancer detection. The spectral signatures were extracted and evaluated in both cancerous and normal tissue. Least squares support vector machines were developed and evaluated for classifying hyperspectral data in order to enhance the detection of cancer tissue. This method was used to detect prostate cancer in tumor-bearing mice and on pathology slides. Spatially resolved images were created to highlight the differences of the reflectance properties of cancer versus those of normal tissue. Preliminary results with 11 mice showed that the sensitivity and specificity of the hyperspectral image classification method are 92.8% to 2.0% and 96.9% to 1.3%, respectively. Therefore, this imaging method may be able to help physicians to dissect malignant regions with a safe margin and to evaluate the tumor bed after resection. This pilot study may lead to advances in the optical diagnosis of prostate cancer using HSI technology.
AD - Emory University, Department of Radiology and Imaging Sciences, Atlanta, Georgia 30329, USA.
AN - 22894488
AU - Akbari, H.
AU - Halig, L. V.
AU - Schuster, D. M.
AU - Osunkoya, A.
AU - Master, V.
AU - Nieh, P. T.
AU - Chen, G. Z.
AU - Fei, B.
C2 - 3608529
DA - Jul
DO - 10.1117/1.JBO.17.7.076005 [doi]
DP - Nlm
ET - 2012/08/17
KW - Algorithms
Animals
Artificial Intelligence
Cell Line, Tumor
Image Enhancement/methods
Image Interpretation, Computer-Assisted/ methods
Male
Mice
Mice, Nude
Optical Imaging/ methods
Pattern Recognition, Automated/ methods
Prostatic Neoplasms/ pathology
Reproducibility of Results
Sensitivity and Specificity
Spectrum Analysis/ methods
L1 - internal-pdf://3356260668/Akbari-2012-Hyperspectral imaging and quantita.pdf
LA - eng
M1 - 7
N1 - Akbari, Hamed
Halig, Luma V
Schuster, David M
Osunkoya, Adeboye
Master, Viraj
Nieh, Peter T
Chen, Georgia Z
Fei, Baowei
P50CA128301/CA/NCI NIH HHS/United States
P50CA128613/CA/NCI NIH HHS/United States
R01 CA156775/CA/NCI NIH HHS/United States
R01CA156775/CA/NCI NIH HHS/United States
UL1 RR025008/RR/NCRR NIH HHS/United States
Research Support, N.I.H., Extramural
United States
Journal of biomedical optics
J Biomed Opt. 2012 Jul;17(7):076005. doi: 10.1117/1.JBO.17.7.076005.
PY - 2012
SN - 1560-2281 (Electronic)
1083-3668 (Linking)
SP - 076005
ST - Hyperspectral imaging and quantitative analysis for prostate cancer detection
T2 - J Biomed Opt
TI - Hyperspectral imaging and quantitative analysis for prostate cancer detection
UR - http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3608529/pdf/JBO-017-076005.pdf
VL - 17
ID - 268
ER -
TY - JOUR
AB - The proposed macroscopic optical histopathology includes a broad-band light source which is selected to illuminate the tissue glass slide of suspicious pathology, and a hyperspectral camera that captures all wavelength bands from 450 to 950 nm. The system has been trained to classify each histologic slide based on predetermined pathology with light having a wavelength within a predetermined range of wavelengths. This technology is able to capture both the spatial and spectral data of tissue. Highly metastatic human head and neck cancer cells were transplanted to nude mice. After 2-3 weeks, the mice were euthanized and the lymph nodes and lung tissues were sent to pathology. The metastatic cancer is studied in lymph nodes and lungs. The pathological slides were imaged using the hyperspectral camera. The results of the proposed method were compared to the pathologic report. Using hyperspectral images, a library of spectral signatures for different tissues was created. The high-dimensional data were classified using a support vector machine (SVM). The spectra are extracted in cancerous and non-cancerous tissues in lymph nodes and lung tissues. The spectral dimension is used as the input of SVM. Twelve glasses are employed for training and evaluation. The leave-one-out cross-validation method is used in the study. After training, the proposed SVM method can detect the metastatic cancer in lung histologic slides with the specificity of 97.7% and the sensitivity of 92.6%, and in lymph node slides with the specificity of 98.3% and the sensitivity of 96.2%. This method may be able to help pathologists to evaluate many histologic slides in a short time.
AD - Department of Radiology and Imaging Sciences, Emory University and Georgia Institute of Technology, Atlanta, GA.
AN - 23336061
AU - Akbari, H.
AU - Halig, L. V.
AU - Zhang, H.
AU - Wang, D.
AU - Chen, Z. G.
AU - Fei, B.
C2 - 3546351
DO - 10.1117/12.912026 [doi]
DP - Nlm
ET - 2013/01/22
L1 - internal-pdf://1289146543/Akbari-2012-Detection of Cancer Metastasis Usi.pdf
LA - Eng
N1 - Akbari, Hamed
Halig, Luma V
Zhang, Hongzheng
Wang, Dongsheng
Chen, Zhuo Georgia
Fei, Baowei
R01 CA156775/CA/NCI NIH HHS/United States
Proceedings of SPIE
Nihms432042
Proc SPIE. 2012;8317:831711. Epub 2012 Mar 23.
PY - 2012
SN - 1996-756X (Print)
1996-756X (Linking)
SP - 831711
ST - Detection of Cancer Metastasis Using a Novel Macroscopic Hyperspectral Method
T2 - Proc SPIE
TI - Detection of Cancer Metastasis Using a Novel Macroscopic Hyperspectral Method
UR - http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3546351/pdf/nihms432042.pdf
VL - 8317
ID - 273
ER -
TY - JOUR
AB - Systematic transrectal ultrasound (TRUS)-guided biopsy is the standard method for a definitive diagnosis of prostate cancer. However, this biopsy approach uses two-dimensional (2D) ultrasound images to guide biopsy and can miss up to 30% of prostate cancers. We are developing a molecular image-directed, three-dimensional (3D) ultrasound image-guided biopsy system for improved detection of prostate cancer. The system consists of a 3D mechanical localization system and software workstation for image segmentation, registration, and biopsy planning. In order to plan biopsy in a 3D prostate, we developed an automatic segmentation method based wavelet transform. In order to incorporate PET/CT images into ultrasound-guided biopsy, we developed image registration methods to fuse TRUS and PET/CT images. The segmentation method was tested in ten patients with a DICE overlap ratio of 92.4% +/- 1.1 %. The registration method has been tested in phantoms. The biopsy system was tested in prostate phantoms and 3D ultrasound images were acquired from two human patients. We are integrating the system for PET/CT directed, 3D ultrasound-guided, targeted biopsy in human patients.
AD - Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA 30329.
AN - 22708023
AU - Fei, B.
AU - Schuster, D. M.
AU - Master, V.
AU - Akbari, H.
AU - Fenster, A.
AU - Nieh, P.
C2 - 3375601
DO - 10.1117/12.912182 [doi]
DP - Nlm
ET - 2012/06/19
LA - Eng
N1 - Fei, Baowei
Schuster, David M
Master, Viraj
Akbari, Hamed
Fenster, Aaron
Nieh, Peter
R01 CA156775/CA/NCI NIH HHS/United States
R01 CA156775-01/CA/NCI NIH HHS/United States
R01 CA156775-02/CA/NCI NIH HHS/United States
R01 CA156775-03/CA/NCI NIH HHS/United States
Proceedings of SPIE
Nihms362795
Proc SPIE. 2012;2012. pii: 831613. Epub 2012 Feb 16.
PY - 2012
SN - 1996-756X (Print)
1996-756X (Linking)
ST - A Molecular Image-directed, 3D Ultrasound-guided Biopsy System for the Prostate
T2 - Proc SPIE
TI - A Molecular Image-directed, 3D Ultrasound-guided Biopsy System for the Prostate
UR - http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=1346064
VL - 2012
ID - 274
ER -
TY - JOUR
AB - PURPOSE: Combined MRPET is a relatively new, hybrid imaging modality. A human MRPET prototype system consisting of a Siemens 3T Trio MR and brain PET insert was installed and tested at our institution. Its present design does not offer measured attenuation correction (AC) using traditional transmission imaging. This study is the development of quantification tools including MR-based AC for quantification in combined MRPET for brain imaging. METHODS: The developed quantification tools include image registration, segmentation, classification, and MR-based AC. These components were integrated into a single scheme for processing MRPET data. The segmentation method is multiscale and based on the Radon transform of brain MR images. It was developed to segment the skull on T1-weighted MR images. A modified fuzzy C-means classification scheme was developed to classify brain tissue into gray matter, white matter, and cerebrospinal fluid. Classified tissue is assigned an attenuation coefficient so that AC factors can be generated. PET emission data are then reconstructed using a three-dimensional ordered sets expectation maximization method with the MR-based AC map. Ten subjects had separate MR and PET scans. The PET with [(11)C]PIB was acquired using a high-resolution research tomography (HRRT) PET. MR-based AC was compared with transmission (TX)-based AC on the HRRT. Seventeen volumes of interest were drawn manually on each subject image to compare the PET activities between the MR-based and TX-based AC methods. RESULTS: For skull segmentation, the overlap ratio between our segmented results and the ground truth is 85.2 +/- 2.6%. Attenuation correction results from the ten subjects show that the difference between the MR and TX-based methods was <6.5%. CONCLUSIONS: MR-based AC compared favorably with conventional transmission-based AC. Quantitative tools including registration, segmentation, classification, and MR-based AC have been developed for use in combined MRPET.
AD - Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA, USA. bfei@emory.edu
AN - 23039679
AU - Fei, B.
AU - Yang, X.
AU - Nye, J. A.
AU - Aarsvold, J. N.
AU - Raghunath, N.
AU - Cervo, M.
AU - Stark, R.
AU - Meltzer, C. C.
AU - Votaw, J. R.
C2 - 3477199
DA - Oct
DO - 10.1118/1.4754796 [doi]
DP - Nlm
ET - 2012/10/09
KW - Algorithms
Humans
Image Processing, Computer-Assisted/ methods
Magnetic Resonance Imaging/ methods
Phantoms, Imaging
Positron-Emission Tomography/ methods
L1 - internal-pdf://3846539197/Fei-2012-MRPET quantification tools_ registrat.pdf
LA - eng
M1 - 10
N1 - Fei, Baowei
Yang, Xiaofeng
Nye, Jonathon A
Aarsvold, John N
Raghunath, Nivedita
Cervo, Morgan
Stark, Rebecca
Meltzer, Carolyn C
Votaw, John R
P50CA128301/CA/NCI NIH HHS/United States
P50CA128613/CA/NCI NIH HHS/United States
R01 CA156775/CA/NCI NIH HHS/United States
R01CA156775/CA/NCI NIH HHS/United States
UL1 RR025008/RR/NCRR NIH HHS/United States
UL1RR025008/RR/NCRR NIH HHS/United States
Research Support, N.I.H., Extramural
United States
Medical physics
Med Phys. 2012 Oct;39(10):6443-54. doi: 10.1118/1.4754796.
PY - 2012
SN - 0094-2405 (Print)
0094-2405 (Linking)
SP - 6443-54
ST - MRPET quantification tools: registration, segmentation, classification, and MR-based attenuation correction
T2 - Med Phys
TI - MRPET quantification tools: registration, segmentation, classification, and MR-based attenuation correction
UR - http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3477199/pdf/MPHYA6-000039-006443_1.pdf
VL - 39
ID - 265
ER -
TY - JOUR
AB - Cardiovascular disease is the leading cause of global mortality, yet its early detection remains a vexing problem of modern medicine. Although the computed tomography (CT) calcium score predicts cardiovascular risk, relatively high cost ($250-400) and radiation dose (1-3 mSv) limit its universal utility as a screening tool. Dual-energy digital subtraction radiography (DE; <$60, 0.07 mSv) enables detection of calcified structures with high sensitivity. In this pilot study, we examined DE radiography's ability to quantify coronary artery calcification (CAC). We identified 25 patients who underwent non-contrast CT and DE chest imaging performed within 12 months using documented CAC as the major inclusion criteria. A DE calcium score was developed based on pixel intensity multiplied by the area of the calcified plaque. DE scores were plotted against CT scores. Subsequently, a validation cohort of 14 additional patients was independently evaluated to confirm the accuracy and precision of CAC quantification, yielding a total of 39 subjects. Among all subjects (n = 39), the DE score demonstrated a correlation coefficient of 0.87 (p < 0.0001) when compared with the CT score. For the 13 patients with CT scores of <400, the correlation coefficient was -0.26. For the 26 patients with CT scores of >/=400, the correlation coefficient yielded 0.86. This pilot study demonstrates the feasibility of DE radiography to identify patients at the highest cardiovascular risk. DE radiography's accuracy at lower scores remains unclear. Further evaluation of DE radiography as an inexpensive and low-radiation imaging tool to diagnose cardiovascular disease appears warranted.
AD - Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA.
AN - 21557030
AU - Mafi, J. N.
AU - Fei, B.
AU - Roble, S.
AU - Dota, A.
AU - Katrapati, P.
AU - Bezerra, H. G.
AU - Wang, H.
AU - Wang, W.
AU - Ciancibello, L.
AU - Costa, M.
AU - Simon, D. I.
AU - Orringer, C. E.
AU - Gilkeson, R. C.
C2 - 3264713
DA - Feb
DO - 10.1007/s10278-011-9385-y [doi]
DP - Nlm
ET - 2011/05/11
KW - Angiography, Digital Subtraction/ methods
Calcinosis/ radiography
Case-Control Studies
Coronary Angiography/methods
Coronary Artery Disease/physiopathology/ radiography
Feasibility Studies
Female
Humans
Male
Middle Aged
Pilot Projects
Reproducibility of Results
Retrospective Studies
Sensitivity and Specificity
Severity of Illness Index
Statistics, Nonparametric
L1 - internal-pdf://1164879117/Mafi-2012-Assessment of coronary artery calciu.pdf
LA - eng
M1 - 1
N1 - Mafi, John N
Fei, Baowei
Roble, Sharon
Dota, Anthony
Katrapati, Prashanth
Bezerra, Hiram G
Wang, Hesheng
Wang, Wei
Ciancibello, Leslie
Costa, Marco
Simon, Daniel I
Orringer, Carl E
Gilkeson, Robert C
R21 CA120536/CA/NCI NIH HHS/United States
R21CA120536/CA/NCI NIH HHS/United States
Comparative Study
Research Support, N.I.H., Extramural
United States
Journal of digital imaging
J Digit Imaging. 2012 Feb;25(1):129-36. doi: 10.1007/s10278-011-9385-y.
PY - 2012
SN - 1618-727X (Electronic)
0897-1889 (Linking)
SP - 129-36
ST - Assessment of coronary artery calcium using dual-energy subtraction digital radiography
T2 - J Digit Imaging
TI - Assessment of coronary artery calcium using dual-energy subtraction digital radiography
UR - http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3264713/pdf/10278_2011_Article_9385.pdf
VL - 25
ID - 271
ER -
TY - JOUR
AB - PURPOSE: To compare the estimate of normalized glandular dose in mammography and breast CT imaging obtained using the actual glandular tissue distribution in the breast to that obtained using the homogeneous tissue mixture approximation. METHODS: Twenty volumetric images of patient breasts were acquired with a dedicated breast CT prototype system and the voxels in the breast CT images were automatically classified into skin, adipose, and glandular tissue. The breasts in the classified images underwent simulated mechanical compression to mimic the conditions present during mammographic acquisition. The compressed thickness for each breast was set to that achieved during each patient's last screening cranio-caudal (CC) acquisition. The volumetric glandular density of each breast was computed using both the compressed and uncompressed classified images, and additional images were created in which all voxels representing adipose and glandular tissue were replaced by a homogeneous mixture of these two tissues in a proportion corresponding to each breast's volumetric glandular density. All four breast images (compressed and uncompressed; heterogeneous and homogeneous tissue) were input into Monte Carlo simulations to estimate the normalized glandular dose during mammography (compressed breasts) and dedicated breast CT (uncompressed breasts). For the mammography simulations the x-ray spectra used was that used during each patient's last screening CC acquisition. For the breast CT simulations, two x-ray spectra were used, corresponding to the x-ray spectra with the lowest and highest energies currently being used in dedicated breast CT prototype systems under clinical investigation. The resulting normalized glandular dose for the heterogeneous and homogeneous versions of each breast for each modality was compared. RESULTS: For mammography, the normalized glandular dose based on the homogeneous tissue approximation was, on average, 27% higher than that estimated using the true heterogeneous glandular tissue distribution (Wilcoxon Signed Rank Test p = 0.00046). For dedicated breast CT, the overestimation of normalized glandular dose was, on average, 8% (49 kVp spectrum, p = 0.00045) and 4% (80 kVp spectrum, p = 0.000089). Only two cases in mammography and two cases in dedicated breast CT with a tube voltage of 49 kVp resulted in lower dose estimates for the homogeneous tissue approximation compared to the heterogeneous tissue distribution. CONCLUSIONS: The normalized glandular dose based on the homogeneous tissue mixture approximation results in a significant overestimation of dose to the imaged breast. This overestimation impacts the use of dose estimates in absolute terms, such as for risk estimates, and may impact some comparative studies, such as when modalities or techniques with different x-ray energies are used. The error introduced by the homogeneous tissue mixture approximation in higher energy x-ray modalities, such as dedicated breast CT, although statistically significant, may not be of clinical concern. Further work is required to better characterize this overestimation and potentially develop new metrics or correction factors to better estimate the true glandular dose to breasts undergoing imaging with ionizing radiation.
AD - Department of Radiology and Imaging Sciences and Winship Cancer Institute, Emory University School of Medicine, 1701 Upper Gate Drive Northeast, Suite 5018, Atlanta, Georgia 30322, USA. isechop@emory.edu
AN - 22894430
AU - Sechopoulos, I.
AU - Bliznakova, K.
AU - Qin, X.
AU - Fei, B.
AU - Feng, S. S.
C2 - 3416880
DA - Aug
DO - 10.1118/1.4737025 [doi]
DP - Nlm
ET - 2012/08/17
KW - Breast/pathology
Breast Neoplasms/ diagnosis/ radiography
Computer Simulation
Female
Humans
Mammography/methods
Models, Statistical
Monte Carlo Method
Radiation, Ionizing
Radiometry/ methods
Reproducibility of Results
Tissue Distribution
Tomography, X-Ray Computed/ methods
X-Rays
L1 - internal-pdf://3377883773/Sechopoulos-2012-Characterization of the homog.pdf
LA - eng
M1 - 8
N1 - Sechopoulos, Ioannis
Bliznakova, Kristina
Qin, Xulei
Fei, Baowei
Feng, Steve Si Jia
P50CA128301/CA/NCI NIH HHS/United States
R01 CA156775/CA/NCI NIH HHS/United States
R01 CA163746/CA/NCI NIH HHS/United States
R01CA156775/CA/NCI NIH HHS/United States
R01CA163746/CA/NCI NIH HHS/United States
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
United States
Medical physics
Med Phys. 2012 Aug;39(8):5050-9. doi: 10.1118/1.4737025.
PY - 2012
SN - 0094-2405 (Print)
0094-2405 (Linking)
SP - 5050-9
ST - Characterization of the homogeneous tissue mixture approximation in breast imaging dosimetry
T2 - Med Phys
TI - Characterization of the homogeneous tissue mixture approximation in breast imaging dosimetry
UR - http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3416880/pdf/MPHYA6-000039-005050_1.pdf
VL - 39
ID - 267
ER -
TY - JOUR
AB - PURPOSE: Partial volume effect in positron emission tomography (PET) can cause incorrect quantification of radiopharmaceutical uptake in functional imaging. A PET partial volume correction method is presented to attenuate partial volume blurring and to yield voxel-based corrected PET images. METHODS: By modeling partial volume effect as a convolution of point spread function of the PET scanner, the reconstructed PET images are corrected by iterative deconvolution with an edge-preserving smoothness constraint. The constraint is constructed to restore discontinuities extracted from coregistered MR images but maintains the smoothness in radioactivity distribution. The correction is implemented in a Bayesian deconvolution framework and is solved by a conjugate gradient method. The performance of the method was compared with the geometric transfer matrix (GTM) method on a simulated dataset. The method was evaluated on synthesized brain FDG-PET data and phantom MRI-PET experiments. RESULTS: The true PET activity of objects with a size of greater than the full-width at half maximum of the point spread function has been effectively restored in the simulated data. The partial volume correction method is quantitatively comparable to the GTM method. For synthesized FDG-PET with true activity 0 muci/cc for cerebrospinal fluid (CSF), 228 muci/cc for white matter (WM), and 621 muci/cc for gray matter (GM), the method has improved the radioactivity quantification from 186 +/- 16 muci/cc to 30 +/- 7 muci/cc in CSF, 317 +/- 15 muci/cc to 236 +/- 10 muci/cc for WM, 438 +/- 4 muci/cc to 592 +/- 5 muci/cc for GM. Both visual and quantitative assessments show improvement of partial volume correction in the synthesized and phantom experiments. CONCLUSIONS: The partial volume correction method improves the quantification of PET images. The method is comparable to the GTM method but does not need MR image segmentation or prior tracer distribution information. The voxel-based method can be particularly useful for combined PET/MRI studies.
AD - Department of Radiology and Imaging Sciences, Emory University, Atlanta, Georgia 30329, USA.
AN - 22225287
AU - Wang, H.
AU - Fei, B.
C2 - 3261055
DA - Jan
DO - 10.1118/1.3665704 [doi]
DP - Nlm
ET - 2012/01/10
KW - Algorithms
Artifacts
Brain/anatomy & histology/ radionuclide imaging
Humans
Image Enhancement/ methods
Image Interpretation, Computer-Assisted/ methods
Imaging, Three-Dimensional/ methods
Magnetic Resonance Imaging/ methods
Positron-Emission Tomography/ methods
Reproducibility of Results
Sensitivity and Specificity
L1 - internal-pdf://3196894043/Wang-2012-An MR image-guided, voxel-based part.pdf
LA - eng
M1 - 1
N1 - Wang, Hesheng
Fei, Baowei
P50CA128301/CA/NCI NIH HHS/United States
P50CA128613/CA/NCI NIH HHS/United States
R01 CA156775/CA/NCI NIH HHS/United States
R01CA156775/CA/NCI NIH HHS/United States
R21 CA120536/CA/NCI NIH HHS/United States
UL1 RR015008/RR/NCRR NIH HHS/United States
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
United States
Medical physics
Med Phys. 2012 Jan;39(1):179-95. doi: 10.1118/1.3665704.
PY - 2012
SN - 0094-2405 (Print)
0094-2405 (Linking)
SP - 179-95
ST - An MR image-guided, voxel-based partial volume correction method for PET images
T2 - Med Phys
TI - An MR image-guided, voxel-based partial volume correction method for PET images
UR - http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3261055/pdf/MPHYA6-000039-000179_1.pdf
VL - 39
ID - 272
ER -
TY - JOUR
AB - We developed a three-dimensional (3D) segmentation method for transrectal ultrasound (TRUS) images, which is based on longitudinal image registration and machine learning. Using longitudinal images of each individual patient, we register previously acquired images to the new images of the same subject. Three orthogonal Gabor filter banks were used to extract texture features from each registered image. Patient-specific Gabor features from the registered images are used to train kernel support vector machines (KSVMs) and then to segment the newly acquired prostate image. The segmentation method was tested in TRUS data from five patients. The average surface distance between our and manual segmentation is 1.18 +/- 0.31 mm, indicating that our automatic segmentation method based on longitudinal image registration is feasible for segmenting the prostate in TRUS images.
AD - Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA.
AN - 24027622
AU - Yang, X.
AU - Fei, B.
C2 - 3767004
DA - Feb 23
DO - 10.1117/12.912188 [doi]
DP - Nlm
ET - 2012/02/23
L1 - internal-pdf://4260075164/Yang-2012-3D Prostate Segmentation of Ultrasou.pdf
LA - Eng
N1 - Yang, Xiaofeng
Fei, Baowei
R01 CA156775/CA/NCI NIH HHS/United States
R01 CA156775-01/CA/NCI NIH HHS/United States
R01 CA156775-02/CA/NCI NIH HHS/United States
R01 CA156775-03/CA/NCI NIH HHS/United States
Proceedings of SPIE
Nihms362793
Proc SPIE. 2012 Feb 23;8316:83162O.
PY - 2012
SN - 1996-756X (Print)
1996-756X (Linking)
SP - 83162O
ST - 3D Prostate Segmentation of Ultrasound Images Combining Longitudinal Image Registration and Machine Learning
T2 - Proc SPIE
TI - 3D Prostate Segmentation of Ultrasound Images Combining Longitudinal Image Registration and Machine Learning
UR - http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3767004/pdf/nihms362793.pdf
VL - 8316
ID - 270
ER -
TY - JOUR
AB - We have applied image analysis methods in the assessment of human kidney perfusion based on 3D dynamic contrast-enhanced (DCE) MRI data. This approach consists of 3D non-rigid image registration of the kidneys and fuzzy C-mean classification of kidney tissues. The proposed registration method reduced motion artifacts in the dynamic images and improved the analysis of kidney compartments (cortex, medulla, and cavities). The dynamic intensity curves show the successive transition of the contrast agent through kidney compartments. The proposed method for motion correction and kidney compartment classification may be used to improve the validity and usefulness of further model-based pharmacokinetic analysis of kidney function.
AD - Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA.
AN - 22468206
AU - Yang, X.
AU - Ghafourian, P.
AU - Sharma, P.
AU - Salman, K.
AU - Martin, D.
AU - Fei, B.
C2 - 3314431
DO - 10.1117/12.912190 [doi]
DP - Nlm
ET - 2012/04/03
L1 - internal-pdf://3935500019/Yang-2012-Nonrigid Registration and Classifica.pdf
LA - Eng
N1 - Yang, Xiaofeng
Ghafourian, Pegah
Sharma, Puneet
Salman, Khalil
Martin, Diego
Fei, Baowei
R01 CA156775/CA/NCI NIH HHS/United States
R01 CA156775-01/CA/NCI NIH HHS/United States
R01 CA156775-02/CA/NCI NIH HHS/United States
R01 CA156775-03/CA/NCI NIH HHS/United States
Proceedings of SPIE
Nihms362796
Proc SPIE. 2012;8314:83140B. Epub 2012 Feb 13.
PY - 2012
SN - 1996-756X (Print)
1996-756X (Linking)
SP - 83140B
ST - Nonrigid Registration and Classification of the Kidneys in 3D Dynamic Contrast Enhanced (DCE) MR Images
T2 - Proc SPIE
TI - Nonrigid Registration and Classification of the Kidneys in 3D Dynamic Contrast Enhanced (DCE) MR Images
UR - http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3314431/pdf/nihms362796.pdf
VL - 8314
ID - 275
ER -
TY - JOUR
AB - PURPOSE: To develop and test an automated algorithm to classify the different tissues present in dedicated breast CT images. METHODS: The original CT images are first corrected to overcome cupping artifacts, and then a multiscale bilateral filter is used to reduce noise while keeping edge information on the images. As skin and glandular tissues have similar CT values on breast CT images, morphologic processing is used to identify the skin mask based on its position information. A modified fuzzy C-means (FCM) classification method is then used to classify breast tissue as fat and glandular tissue. By combining the results of the skin mask with the FCM, the breast tissue is classified as skin, fat, and glandular tissue. To evaluate the authors' classification method, the authors use Dice overlap ratios to compare the results of the automated classification to those obtained by manual segmentation on eight patient images. RESULTS: The correction method was able to correct the cupping artifacts and improve the quality of the breast CT images. For glandular tissue, the overlap ratios between the authors' automatic classification and manual segmentation were 91.6% +/- 2.0%. CONCLUSIONS: A cupping artifact correction method and an automatic classification method were applied and evaluated for high-resolution dedicated breast CT images. Breast tissue classification can provide quantitative measurements regarding breast composition, density, and tissue distribution.
AD - Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA 30329, USA.
AN - 23039675
AU - Yang, X.
AU - Wu, S.
AU - Sechopoulos, I.
AU - Fei, B.
C2 - 3477198
DA - Oct
DO - 10.1118/1.4754654 [doi]
DP - Nlm
ET - 2012/10/09
KW - Artifacts
Automation
Breast/ cytology/pathology
Humans
Image Processing, Computer-Assisted/ methods
Mammography/ methods
Phantoms, Imaging
Tomography, X-Ray Computed/ methods
L1 - internal-pdf://2957007884/Yang-2012-Cupping artifact correction and auto.pdf
LA - eng
M1 - 10
N1 - Yang, Xiaofeng
Wu, Shengyong
Sechopoulos, Ioannis
Fei, Baowei
P50CA128301/CA/NCI NIH HHS/United States
P50CA128613/CA/NCI NIH HHS/United States
R01 CA156775/CA/NCI NIH HHS/United States
R01 CA163746/CA/NCI NIH HHS/United States
R01CA156775/CA/NCI NIH HHS/United States
R01CA163746/CA/NCI NIH HHS/United States
UL1 RR025008/RR/NCRR NIH HHS/United States
Research Support, N.I.H., Extramural
United States
Medical physics
Med Phys. 2012 Oct;39(10):6397-406. doi: 10.1118/1.4754654.
PY - 2012
SN - 0094-2405 (Print)
0094-2405 (Linking)
SP - 6397-406
ST - Cupping artifact correction and automated classification for high-resolution dedicated breast CT images
T2 - Med Phys
TI - Cupping artifact correction and automated classification for high-resolution dedicated breast CT images
UR - http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3477198/pdf/MPHYA6-000039-006397_1.pdf
VL - 39
ID - 266
ER -
TY - JOUR
AB - Numerical estimation of the size of the kidney is useful in evaluating conditions of the kidney, especially, when serial MR imaging is performed to evaluate the kidney function. This paper presents a new method for automatic segmentation of the kidney in three-dimensional (3D) MR images, by extracting texture features and statistical matching of geometrical shape of the kidney. A set of Wavelet-based support vector machines (W-SVMs) is trained on the MR images. The W-SVMs capture texture priors of MRI for classification of the kidney and non-kidney tissues in different zones around the kidney boundary. In the segmentation procedure, these W-SVMs are trained to tentatively label each voxel around the kidney model as a kidney or non-kidney voxel by texture matching. A probability kidney model is created using 10 segmented MRI data. The model is initially localized based on the intensity profiles in three directions. The weight functions are defined for each labeled voxel for each Wavelet-based, intensity-based, and model-based label. Consequently, each voxel has three labels and three weights for the Wavelet feature, intensity, and probability model. Using a 3D edge detection method, the model is re-localized and the segmented kidney is modified based on a region growing method in the model region. The probability model is re-localized based on the results and this loop continues until the segmentation converges. Experimental results with mouse MRI data show the good performance of the proposed method in segmenting the kidney in MR images.
AD - Department of Radiology and Imaging Sciences, Emory University and Georgia Institute of Technology, Atlanta, GA.
AN - 24027620
AU - Akbari, H.
AU - Fei, B.
C2 - 3766988
DA - Feb 23
DO - 10.1117/12.912028 [doi]
DP - Nlm
ET - 2013/09/13
L1 - internal-pdf://3755270528/Akbari-2013-Automatic 3D Segmentation of the K.pdf
LA - Eng
N1 - Akbari, Hamed
Fei, Baowei
R01 CA156775/CA/NCI NIH HHS/United States
R01 CA156775-01/CA/NCI NIH HHS/United States
R01 CA156775-02/CA/NCI NIH HHS/United States
R01 CA156775-03/CA/NCI NIH HHS/United States
Proceedings of SPIE
Nihms362797
Proc SPIE. 2013 Feb 23;8314:83143D.
PY - 2013
SN - 1996-756X (Print)
1996-756X (Linking)
SP - 83143D
ST - Automatic 3D Segmentation of the Kidney in MR Images Using Wavelet Feature Extraction and Probability Shape Model
T2 - Proc SPIE
TI - Automatic 3D Segmentation of the Kidney in MR Images Using Wavelet Feature Extraction and Probability Shape Model
UR - http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3766988/pdf/nihms-362797.pdf
VL - 8314
ID - 262
ER -
TY - JOUR
AB - Multimodatity imaging is a promising approach for improving prostate cancer detection and diagnosis. This article describes various concepts in PET-directed, ultrasound-guided biopsies and highlights a new PET/ultrasound fusion targeted biopsy system for prostate cancer detection.
AD - Department of Radiology and Imaging Sciences, Emory University, 1841 Clifton Road NE, Atlanta, GA 30329, USA.
Department of Urology, Emory University, 1365 Clifton Road NE, Atlana, GA 30322.
Department of Radiology and Imaging Sciences, Emory University, 1841 Clifton Road NE, Atlana, GA 30329.
AN - 25392702
AU - Fei, B.
AU - Nieh, P. T.
AU - Schuster, D. M.
AU - Master, V. A.
C2 - 4225556
DA - Jan
DP - Nlm
ET - 2013/01/01
L1 - internal-pdf://3576057227/Fei-2013-PET-directed, 3D Ultrasound-guided pr.pdf
LA - Eng
M1 - 1
N1 - Fei, Baowei
Nieh, Peter T
Schuster, David M
Master, Viraj A
R01 CA156775/CA/NCI NIH HHS/United States
Diagnostic imaging Europe
Nihms514152
Diagn Imaging Eur. 2013 Jan;29(1):12-15.
PY - 2013
SN - 1461-0051 (Print)
1461-0051 (Linking)
SP - 12-15
ST - PET-directed, 3D Ultrasound-guided prostate biopsy
T2 - Diagn Imaging Eur
TI - PET-directed, 3D Ultrasound-guided prostate biopsy
UR - http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4225556/pdf/nihms514152.pdf
VL - 29
ID - 264
ER -
TY - JOUR
AB - Photodynamictherapy (PDT) uses a drug called a photosensitizer that is excited by irradiation with a laser light of a particular wavelength, which generates reactive singlet oxygen that damages the tumor cells. The photosensitizer and light are inert; therefore, systemic toxicities are minimized in PDT. The synthesis of novel PDT drugs and the use of nanosized carriers for photosensitizers may improve the efficiency of the therapy and the delivery of the drug. In this study, we formulated two nanoparticles with and without a targeting ligand to encapsulate phthalocyanines 4 (Pc 4) molecule and compared their biodistributions. Metastatic human head and neck cancer cells (M4e) were transplanted into nude mice. After 2-3 weeks, the mice were injected with Pc 4, Pc 4 encapsulated into surface coated iron oxide (IO-Pc 4), and IO-Pc 4 conjugated with a fibronectin-mimetic peptide (FMP-IO-Pc 4) which binds specifically to integrin beta1. The mice were imaged using a multispectral camera. Using multispectral images, a library of spectral signatures was created and the signal per pixel of each tumor was calculated, in a grayscale representation of the unmixed signal of each drug. An enhanced biodistribution of nanoparticle encapsulated PDT drugs compared to non-formulated Pc 4 was observed. Furthermore, specific targeted nanoparticles encapsulated Pc 4 has a quicker delivery time and accumulation in tumor tissue than the non-targeted nanoparticles. The nanoparticle-encapsulated PDT drug can have a variety of potential applications in cancer imaging and treatment.
AD - Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA.
AN - 24236230
AU - Halig, L. V.
AU - Wang, D.
AU - Wang, A. Y.
AU - Chen, Z. G.
AU - Fei, B.
C2 - 3824266
DA - Mar 29
DO - 10.1117/12.2006492 [doi]
DP - Nlm
ET - 2013/11/16
LA - Eng
N1 - Halig, Luma V
Wang, Dongsheng
Wang, Andrew Y
Chen, Zhuo Georgia
Fei, Baowei
R01 CA156775/CA/NCI NIH HHS/United States
R21 CA120536/CA/NCI NIH HHS/United States
Proceedings of SPIE
Nihms514146
Proc SPIE. 2013 Mar 29;8672. doi: 10.1117/12.2006492.
PY - 2013
SN - 1996-756X (Print)
1996-756X (Linking)
ST - Biodistribution Study of Nanoparticle Encapsulated Photodynamic Therapy Drugs Using Multispectral Imaging
T2 - Proc SPIE
TI - Biodistribution Study of Nanoparticle Encapsulated Photodynamic Therapy Drugs Using Multispectral Imaging
UR - http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=1674613
VL - 8672
ID - 259
ER -
TY - JOUR
AB - An automatic segmentation framework is proposed to segment the right ventricle (RV) in echocardiographic images. The method can automatically segment both epicardial and endocardial boundaries from a continuous echocardiography series by combining sparse matrix transform, a training model, and a localized region-based level set. First, the sparse matrix transform extracts main motion regions of the myocardium as eigen-images by analyzing the statistical information of the images. Second, an RV training model is registered to the eigen-images in order to locate the position of the RV. Third, the training model is adjusted and then serves as an optimized initialization for the segmentation of each image. Finally, based on the initializations, a localized, region-based level set algorithm is applied to segment both epicardial and endocardial boundaries in each echocardiograph. Three evaluation methods were used to validate the performance of the segmentation framework. The Dice coefficient measures the overall agreement between the manual and automatic segmentation. The absolute distance and the Hausdorff distance between the boundaries from manual and automatic segmentation were used to measure the accuracy of the segmentation. Ultrasound images of human subjects were used for validation. For the epicardial and endocardial boundaries, the Dice coefficients were 90.8 +/- 1.7% and 87.3 +/- 1.9%, the absolute distances were 2.0 +/- 0.42 mm and 1.79 +/- 0.45 mm, and the Hausdorff distances were 6.86 +/- 1.71 mm and 7.02 +/- 1.17 mm, respectively. The automatic segmentation method based on a sparse matrix transform and level set can provide a useful tool for quantitative cardiac imaging.
AD - Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA 30329, USA.
AN - 24107618
AU - Qin, X.
AU - Cong, Z.
AU - Fei, B.
C2 - 3925785
DA - Nov 7
DO - 10.1088/0031-9155/58/21/7609 [doi]
DP - Nlm
ET - 2013/10/11
KW - Algorithms
Automation
Echocardiography/ methods
Endocardium/ultrasonography
Heart Ventricles/ ultrasonography
Humans
Image Processing, Computer-Assisted/ methods
Pericardium/ultrasonography
L1 - internal-pdf://2051682535/Qin-2013-Automatic segmentation of right ventr.pdf
LA - eng
M1 - 21
N1 - Qin, Xulei
Cong, Zhibin
Fei, Baowei
P50CA128301/CA/NCI NIH HHS/United States
R01 CA156775/CA/NCI NIH HHS/United States
R01CA156775/CA/NCI NIH HHS/United States
R21 CA176684/CA/NCI NIH HHS/United States
R21CA176684/CA/NCI NIH HHS/United States
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
England
Physics in medicine and biology
Nihms539397
Phys Med Biol. 2013 Nov 7;58(21):7609-24. doi: 10.1088/0031-9155/58/21/7609. Epub 2013 Oct 10.
PY - 2013
SN - 1361-6560 (Electronic)
0031-9155 (Linking)
SP - 7609-24
ST - Automatic segmentation of right ventricular ultrasound images using sparse matrix transform and a level set
T2 - Phys Med Biol
TI - Automatic segmentation of right ventricular ultrasound images using sparse matrix transform and a level set
UR - http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3925785/pdf/nihms539397.pdf
VL - 58
ID - 254
ER -
TY - JOUR
AB - An automatic framework is proposed to segment right ventricle on ultrasound images. This method can automatically segment both epicardial and endocardial boundaries from a continuous echocardiography series by combining sparse matrix transform (SMT), a training model, and a localized region based level set. First, the sparse matrix transform extracts main motion regions of myocardium as eigenimages by analyzing statistical information of these images. Second, a training model of right ventricle is registered to the extracted eigenimages in order to automatically detect the main location of the right ventricle and the corresponding transform relationship between the training model and the SMT-extracted results in the series. Third, the training model is then adjusted as an adapted initialization for the segmentation of each image in the series. Finally, based on the adapted initializations, a localized region based level set algorithm is applied to segment both epicardial and endocardial boundaries of the right ventricle from the whole series. Experimental results from real subject data validated the performance of the proposed framework in segmenting right ventricle from echocardiography. The mean Dice scores for both epicardial and endocardial boundaries are 89.1%+/-2.3% and 83.6+/-7.3%, respectively. The automatic segmentation method based on sparse matrix transform and level set can provide a useful tool for quantitative cardiac imaging.
AD - Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA.
AN - 24236228
AU - Qin, X.
AU - Cong, Z.
AU - Halig, L. V.
AU - Fei, B.
C2 - 3824270
DA - Mar 13
DO - 10.1117/12.2006490 [doi]
DP - Nlm
ET - 2013/11/16
LA - Eng
N1 - Qin, Xulei
Cong, Zhibin
Halig, Luma V
Fei, Baowei
R01 CA156775/CA/NCI NIH HHS/United States
Proceedings of SPIE
Nihms514138
Proc SPIE. 2013 Mar 13;8669. doi: 10.1117/12.2006490.
PY - 2013
SN - 1996-756X (Print)
1996-756X (Linking)
ST - Automatic Segmentation of Right Ventricle on Ultrasound Images Using Sparse Matrix Transform and Level Set
T2 - Proc SPIE
TI - Automatic Segmentation of Right Ventricle on Ultrasound Images Using Sparse Matrix Transform and Level Set
UR - http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=1667493
VL - 8669
ID - 261
ER -
TY - JOUR
AB - Cardiac myofiber plays an important role in stress mechanism during heart beating periods. The orientation of myofibers decides the effects of the stress distribution and the whole heart deformation. It is important to image and quantitatively extract these orientations for understanding the cardiac physiological and pathological mechanism and for diagnosis of chronic diseases. Ultrasound has been wildly used in cardiac diagnosis because of its ability of performing dynamic and noninvasive imaging and because of its low cost. An extraction method is proposed to automatically detect the cardiac myofiber orientations from high frequency ultrasound images. First, heart walls containing myofibers are imaged by B-mode high frequency (>20 MHz) ultrasound imaging. Second, myofiber orientations are extracted from ultrasound images using the proposed method that combines a nonlinear anisotropic diffusion filter, Canny edge detector, Hough transform, and K-means clustering. This method is validated by the results of ultrasound data from phantoms and pig hearts.
AD - Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA.
Department of Pediatrics, Emory University School of Medicine, Atlanta, GA.
Department of Surgery, Emory University School of Medicine, Atlanta, GA.
Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA ; Department of Biomedical Engineering, Emory University and Georgia Institute of Technology ; Department of Mathematics & Computer Science, Emory University, Atlanta, GA.
AN - 24392208
AU - Qin, X.
AU - Cong, Z.
AU - Jiang, R.
AU - Shen, M.
AU - Wagner, M. B.
AU - Kishbom, P.
AU - Fei, B.
C2 - 3877319
DA - Mar 29
DO - 10.1117/12.2006494 [doi]
DP - Nlm
ET - 2014/01/07
LA - Eng
N1 - Qin, Xulei
Cong, Zhibin
Jiang, Rong
Shen, Ming
Wagner, Mary B
Kishbom, Paul
Fei, Baowei
R01 CA156775/CA/NCI NIH HHS/United States
Proceedings of SPIE
Nihms514141
Proc SPIE. 2013 Mar 29;8675. doi: 10.1117/12.2006494.
PY - 2013
SN - 1996-756X (Print)
1996-756X (Linking)
ST - Extracting Cardiac Myofiber Orientations from High Frequency Ultrasound Images
T2 - Proc SPIE
TI - Extracting Cardiac Myofiber Orientations from High Frequency Ultrasound Images
UR - http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=1674446
VL - 8675
ID - 258
ER -
TY - JOUR
AB - Anti-1-amino-3-[(18)F] fluorocyclobutane-1-carboxylic acid (anti-3-[(18)F] FACBC) is a synthetic amino acid positron emission tomography (PET) radiotracer with utility in the detection of recurrent prostate carcinoma. The aim of this study is to correlate uptake of anti-3-[(18)F] FACBC with histology of prostatectomy specimens in patients undergoing radical prostatectomy and to determine if uptake correlates to markers of tumor aggressiveness such as Gleason score. Ten patients with prostate carcinoma pre-radical prostatectomy underwent 45 minute dynamic PET-CT of the pelvis after IV injection of 347.8 +/- 81.4 MBq anti-3-[(18)F] FACBC. Each prostate was co-registered to a separately acquired MR, divided into 12 sextants, and analyzed visually for abnormal focal uptake at 4, 16, 28, and 40 min post-injection by a single reader blinded to histology. SUVmax per sextant and total sextant activity (TSA) was also calculated. Histology and Gleason scores were similarly recorded by a urologic pathologist blinded to imaging. Imaging and histologic analysis were then compared. In addition, 3 representative sextants from each prostate were chosen based on highest, lowest and median SUVmax for immunohistochemical (IHC) analysis of Ki67, synaptophysin, P504s, chromogranin A, P53, androgen receptor, and prostein. 79 sextants had malignancy and 41 were benign. Highest combined sensitivity and specificity was at 28 min by visual analysis; 81.3% and 50.0% respectively. SUVmax was significantly higher (p<0.05) for malignant sextants (5.1+/-2.6 at 4 min; 4.5+/-1.6 at 16 min; 4.0+/-1.3 at 28 min; 3.8+/-1.0 at 40 min) compared to non-malignant sextants (4.0+/-1.9 at 4 min; 3.5+/-0.8 at 16 min; 3.4+/-0.9 at 28 min; 3.3+/-0.9 at 40 min), though there was overlap of activity between malignant and non-malignant sextants. SUVmax also significantly correlated (p<0.05) with Gleason score at all time points (r=0.28 at 4 min; r=0.42 at 16 min; r=0.46 at 28 min; r=0.48 at 40 min). There was no significant correlation of anti-3-[(18)F] FACBC SUVmax with Ki-67 or other IHC markers. Since there was no distinct separation between malignant and non-malignant sextants or between Gleason score levels, we believe that anti-3-[(18)F] FACBC PET should not be used alone for radiation therapy planning but may be useful to guide biopsy to the most aggressive lesion.
AD - Department of Radiology and Imaging Sciences, Emory University Atlanta, GA, USA.
AN - 23342303
AU - Schuster, D. M.
AU - Taleghani, P. A.
AU - Nieh, P. T.
AU - Master, V. A.
AU - Amzat, R.
AU - Savir-Baruch, B.
AU - Halkar, R. K.
AU - Fox, T.
AU - Osunkoya, A. O.
AU - Moreno, C. S.
AU - Nye, J. A.
AU - Yu, W.
AU - Fei, B.
AU - Wang, Z.
AU - Chen, Z.
AU - Goodman, M. M.
C2 - 3545368
DP - Nlm
ET - 2013/01/24
L1 - internal-pdf://0680148793/Schuster-2013-Characterization of primary pros.pdf
LA - eng
M1 - 1
N1 - Schuster, David M
Taleghani, Pooneh A
Nieh, Peter T
Master, Viraj A
Amzat, Rianot
Savir-Baruch, Bital
Halkar, Raghuveer K
Fox, Tim
Osunkoya, Adeboye O
Moreno, Carlos S
Nye, Jonathon A
Yu, Weiping
Fei, Baowei
Wang, Zhibo
Chen, Zhengjia
Goodman, Mark M
R01 CA156775/CA/NCI NIH HHS/United States
United States
American journal of nuclear medicine and molecular imaging
Am J Nucl Med Mol Imaging. 2013;3(1):85-96. Epub 2013 Jan 5.
PY - 2013
SN - 2160-8407 (Electronic)
SP - 85-96
ST - Characterization of primary prostate carcinoma by anti-1-amino-2-[(18)F] -fluorocyclobutane-1-carboxylic acid (anti-3-[(18)F] FACBC) uptake
T2 - Am J Nucl Med Mol Imaging
TI - Characterization of primary prostate carcinoma by anti-1-amino-2-[(18)F] -fluorocyclobutane-1-carboxylic acid (anti-3-[(18)F] FACBC) uptake
UR - http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3545368/pdf/ajnmmi0003-0085.pdf
VL - 3
ID - 263
ER -
TY - JOUR
AB - PURPOSE: To analyze the frequency domain characteristics of the signal in mammography images and breast tomosynthesis projections with patient tissue texture due to detected scattered x-rays. METHODS: Acquisitions of x-ray projection images of 19 different patient breasts were simulated using previously acquired volumetric patient images. Acquisition of these images was performed with a dedicated breast CT prototype system, and the images were classified into voxels representing skin, adipose, and glandular tissue with a previously validated automated algorithm. The classified three dimensional images then underwent simulated mechanical compression representing that which is performed during acquisition of mammography and breast tomosynthesis images. The acquisition of projection images of each patient breast was simulated using Monte Carlo methods with each simulation resulting in two images: one of the primary (non-scattered) signal and one of the scatter signal. To analyze the scatter signal for both mammography and breast tomosynthesis, two projections images of each patient breast were simulated, one with the x-ray source positioned at 0 degrees (mammography and central tomosynthesis projection) and at 30 degrees (wide tomosynthesis projection). The noise power spectra (NPS) for both the scatter signal alone and the total signal (primary + scatter) for all images were obtained and the combined results of all patients analyzed. The total NPS was fit to the expected power-law relationship NPS(f) = k/f beta and the results were compared with those previously published on the power spectrum characteristics of mammographic texture. The scatter signal alone was analyzed qualitatively and a power-law fit was also performed. RESULTS: The mammography and tomosynthesis projections of three patient breasts were too small to analyze, so a total of 16 patient breasts were analyzed. The values of beta for the total signal of the 0 degrees projections agreed well with previously published results. As expected, the scatter power spectrum reflected a fast drop-off with increasing spatial frequency, with a reduction of four orders of magnitude by 0.1 lp/mm. The beta values for the scatter signal were 6.14 and 6.39 for the 0 degrees and 30 degrees projections, respectively. CONCLUSIONS: Although the low-frequency characteristics of scatter in mammography and breast tomosynthesis were known, a quantitative analysis of the frequency domain characteristics of this signal was needed in order to optimize previously proposed software-based x-ray scatter reduction algorithms for these imaging modalities.
AD - Departments of Radiology and Imaging Sciences, Hematology and Medical Oncology and Winship Cancer Institute, Emory University, 1701 Upper Gate Drive NE, Suite 5018, Atlanta, Georgia 30322.
AN - 24089907
AU - Sechopoulos, I.
AU - Bliznakova, K.
AU - Fei, B.
C2 - 3785536
DA - Oct
DO - 10.1118/1.4820442 [doi]
DP - Nlm
ET - 2013/10/05
KW - Breast
Humans
Image Processing, Computer-Assisted/ methods
Mammography/ methods
Monte Carlo Method
X-Ray Diffraction
L1 - internal-pdf://1382290406/Sechopoulos-2013-Power spectrum analysis of th.pdf
LA - eng
M1 - 10
N1 - Sechopoulos, Ioannis
Bliznakova, Kristina
Fei, Baowei
P50CA128301/CA/NCI NIH HHS/United States
R01 CA156775/CA/NCI NIH HHS/United States
R01 CA163746/CA/NCI NIH HHS/United States
R01CA156775/CA/NCI NIH HHS/United States
R01CA163746/CA/NCI NIH HHS/United States
R21 CA176684/CA/NCI NIH HHS/United States
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
United States
Medical physics
Med Phys. 2013 Oct;40(10):101905. doi: 10.1118/1.4820442.
PY - 2013
SN - 0094-2405 (Print)
0094-2405 (Linking)
SP - 101905
ST - Power spectrum analysis of the x-ray scatter signal in mammography and breast tomosynthesis projections
T2 - Med Phys
TI - Power spectrum analysis of the x-ray scatter signal in mammography and breast tomosynthesis projections
UR - http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3785536/pdf/MPHYA6-000040-101905_1.pdf
VL - 40
ID - 256
ER -
TY - JOUR
AB - A nonrigid B-spline-based point-matching (BPM) method is proposed to match dense surface points. The method solves both the point correspondence and nonrigid transformation without features extraction. The registration method integrates a motion model, which combines a global transformation and a B-spline-based local deformation, into a robust point-matching framework. The point correspondence and deformable transformation are estimated simultaneously by fuzzy correspondence and by a deterministic annealing technique. Prior information about global translation, rotation and scaling is incorporated into the optimization. A local B-spline motion model decreases the degrees of freedom for optimization and thus enables the registration of a larger number of feature points. The performance of the BPM method has been demonstrated and validated using synthesized 2D and 3D data, mouse MRI and micro-CT images. The proposed BPM method can be used to register feature point sets, 2D curves, 3D surfaces and various image data.
AD - Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA 30329, USA.
AN - 23732538
AU - Wang, H.
AU - Fei, B.
C2 - 3819195
DA - Jun 21
DO - 10.1088/0031-9155/58/12/4315 [doi]
DP - Nlm
ET - 2013/06/05
KW - Animals
Imaging, Three-Dimensional/ methods
Magnetic Resonance Imaging
Mice
Photochemotherapy
Surface Properties
Whole Body Imaging
X-Ray Microtomography
L1 - internal-pdf://4127476648/Wang-2013-Nonrigid point registration for 2D c.pdf
LA - eng
M1 - 12
N1 - Wang, Hesheng
Fei, Baowei
P50CA128301/CA/NCI NIH HHS/United States
R01 CA156775/CA/NCI NIH HHS/United States
R01CA156775/CA/NCI NIH HHS/United States
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
England
Physics in medicine and biology
Nihms491238
Phys Med Biol. 2013 Jun 21;58(12):4315-30. doi: 10.1088/0031-9155/58/12/4315. Epub 2013 Jun 4.
PY - 2013
SN - 1361-6560 (Electronic)
0031-9155 (Linking)
SP - 4315-30
ST - Nonrigid point registration for 2D curves and 3D surfaces and its various applications
T2 - Phys Med Biol
TI - Nonrigid point registration for 2D curves and 3D surfaces and its various applications
UR - http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3819195/pdf/nihms491238.pdf
VL - 58
ID - 257
ER -
TY - JOUR
AB - Early detection of prostate cancer is critical in maximizing the probability of successful treatment. Current systematic biopsy approach takes 12 or more randomly distributed core tissue samples within the prostate and can have a high potential, especially with early disease, for a false negative diagnosis. The purpose of this study is to determine the accuracy of a 3D ultrasound-guided biopsy system. Testing was conducted on prostate phantoms created from an agar mixture which had embedded markers. The phantoms were scanned and the 3D ultrasound system was used to direct the biopsy. Each phantom was analyzed with a CT scan to obtain needle deflection measurements. The deflection experienced throughout the biopsy process was dependent on the depth of the biopsy target. The results for markers at a depth of less than 20 mm, 20-30 mm, and greater than 30 mm were 3.3 mm, 4.7 mm, and 6.2 mm, respectively. This measurement encapsulates the entire biopsy process, from the scanning of the phantom to the firing of the biopsy needle. Increased depth of the biopsy target caused a greater deflection from the intended path in most cases which was due to an angular incidence of the biopsy needle. Although some deflection was present, this system exhibits a clear advantage in the targeted biopsy of prostate cancer and has the potential to reduce the number of false negative biopsies for large lesions.
AD - Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA.
Department of Urology, Emory University School of Medicine, Atlanta, GA.
Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA ; Department of Biomedical Engineering, Emory University and Georgia Institute of Technology ; Department of Mathematics and Computer Science, Emory University, Atlanta, GA.
AN - 24392206
AU - Wooten, W. J., 3rd
AU - Nye, J. A.
AU - Schuster, D. M.
AU - Nieh, P. T.
AU - Master, V. A.
AU - Votaw, J. R.
AU - Fei, B.
C2 - 3877320
DA - Mar 14
DO - 10.1117/12.2007695 [doi]
DP - Nlm
ET - 2014/01/07
LA - Eng
N1 - Wooten, Walter J 3rd
Nye, Jonathan A
Schuster, David M
Nieh, Peter T
Master, Viraj A
Votaw, John R
Fei, Baowei
R01 CA156775/CA/NCI NIH HHS/United States
Proceedings of SPIE
Nihms514136
Proc SPIE. 2013 Mar 14;8671. doi: 10.1117/12.2007695.
PY - 2013
SN - 1996-756X (Print)
1996-756X (Linking)
ST - Accuracy Evaluation of a 3D Ultrasound-guided Biopsy System
T2 - Proc SPIE
TI - Accuracy Evaluation of a 3D Ultrasound-guided Biopsy System
UR - http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=1668869
VL - 8671
ID - 260
ER -
TY - JOUR
AB - BACKGROUND AND OBJECTIVE: Combined magnetic resonance/positron emission tomography (MR/PET) is a relatively new, hybrid imaging modality. MR-based attenuation correction often requires segmentation of the bone on MR images. In this study, we present an automatic segmentation method for the skull on MR images for attenuation correction in brain MR/PET applications. MATERIALS AND METHODS: Our method transforms T1-weighted MR images to the Radon domain and then detects the features of the skull image. In the Radon domain we use a bilateral filter to construct a multiscale image series. For the repeated convolution we increase the spatial smoothing in each scale and make the width of the spatial and range Gaussian function doubled in each scale. Two filters with different kernels along the vertical direction are applied along the scales from the coarse to fine levels. The results from a coarse scale give a mask for the next fine scale and supervise the segmentation in the next fine scale. The use of the multiscale bilateral filtering scheme is to improve the robustness of the method for noise MR images. After combining the two filtered sinograms, the reciprocal binary sinogram of the skull is obtained for the reconstruction of the skull image. RESULTS: This method has been tested with brain phantom data, simulated brain data, and real MRI data. For real MRI data the Dice overlap ratios are 92.2%+/-1.9% between our segmentation and manual segmentation. CONCLUSIONS: The multiscale segmentation method is robust and accurate and can be used for MRI-based attenuation correction in combined MR/PET.
AD - Department of Radiology and Imaging Sciences, Center for Systems Imaging, Emory University, Atlanta, Georgia, USA.
AN - 23761683
AU - Yang, X.
AU - Fei, B.
C2 - 3822115
DA - Nov-Dec
DO - amiajnl-2012-001544 [pii]
10.1136/amiajnl-2012-001544 [doi]
DP - Nlm
ET - 2013/06/14
KW - Brain/ pathology/radionuclide imaging
Diagnosis, Computer-Assisted
Humans
Magnetic Resonance Imaging/ methods
Mathematical Concepts
Phantoms, Imaging
Positron-Emission Tomography/ methods
Skull/ pathology/radionuclide imaging
L1 - internal-pdf://0301270419/Yang-2013-Multiscale segmentation of the skull.pdf
LA - eng
M1 - 6
N1 - Yang, Xiaofeng
Fei, Baowei
P50CA128301/CA/NCI NIH HHS/United States
R01 CA156775/CA/NCI NIH HHS/United States
R01CA156775/CA/NCI NIH HHS/United States
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
United States
Journal of the American Medical Informatics Association : JAMIA
J Am Med Inform Assoc. 2013 Nov-Dec;20(6):1037-45. doi: 10.1136/amiajnl-2012-001544. Epub 2013 Jun 12.
PY - 2013
SN - 1527-974X (Electronic)
1067-5027 (Linking)
SP - 1037-45
ST - Multiscale segmentation of the skull in MR images for MRI-based attenuation correction of combined MR/PET
T2 - J Am Med Inform Assoc
TI - Multiscale segmentation of the skull in MR images for MRI-based attenuation correction of combined MR/PET
UR - http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3822115/pdf/amiajnl-2012-001544.pdf
VL - 20
ID - 255
ER -
TY - JOUR
AB - BACKGROUND: Clinical studies show that metformin attenuates all-cause mortality and myocardial infarction compared with other medications for type 2 diabetes, even at similar glycemic levels. However, there is paucity of data in the euglycemic state on the vasculoprotective effects of metformin. The objectives of this study are to evaluate the effects of metformin on ameliorating atherosclerosis. METHODS AND RESULTS: Using ApoE-/- C57BL/6J mice, we found that metformin attenuates atherosclerosis and vascular senescence in mice fed a high-fat diet and prevents the upregulation of angiotensin II type 1 receptor by a high-fat diet in the aortas of mice. Thus, considering the known deleterious effects of angiotensin II mediated by angiotensin II type 1 receptor, the vascular benefits of metformin may be mediated, at least in part, by angiotensin II type 1 receptor downregulation. Moreover, we found that metformin can cause weight loss without hypoglycemia. We also found that metformin increases the antioxidant superoxide dismutase-1. CONCLUSION: Pleiotropic effects of metformin ameliorate atherosclerosis and vascular senescence.
AD - Division of Cardiology, Emory University School of Medicine, Atlanta, GA
AN - 25527624
AU - Forouzandeh, F.
AU - Salazar, G.
AU - Patrushev, N.
AU - Xiong, S.
AU - Hilenski, L.
AU - Fei, B.
AU - Alexander, R. W.
C2 - 4338706
DA - Dec
DO - jah3786 [pii]
10.1161/JAHA.114.001202 [doi]
DP - Nlm
ET - 2014/12/21
L1 - internal-pdf://2825299478/Forouzandeh-2014-Metformin beyond diabetes_ pl.pdf
LA - eng
M1 - 6
N1 - Forouzandeh, Farshad
Salazar, Gloria
Patrushev, Nikolay
Xiong, Shiqin
Hilenski, Lula
Fei, Baowei
Alexander, R Wayne
Research Support, Non-U.S. Gov't
England
Journal of the American Heart Association
J Am Heart Assoc. 2014 Dec;3(6):e001202. doi: 10.1161/JAHA.114.001202.
PY - 2014
SN - 2047-9980 (Electronic)
2047-9980 (Linking)
SP - e001202
ST - Metformin beyond diabetes: pleiotropic benefits of metformin in attenuation of atherosclerosis
T2 - J Am Heart Assoc
TI - Metformin beyond diabetes: pleiotropic benefits of metformin in attenuation of atherosclerosis
UR - http://jaha.ahajournals.org/content/3/6/e001202.full.pdf
VL - 3
ID - 243
ER -
TY - JOUR
AB - A robust and accurate center-frequency (CF) estimation (RACE) algorithm for improving the performance of the local sine-wave modeling (SinMod) method, which is a good motion estimation method for tagged cardiac magnetic resonance (MR) images, is proposed in this study. The RACE algorithm can automatically, effectively and efficiently produce a very appropriate CF estimate for the SinMod method, under the circumstance that the specified tagging parameters are unknown, on account of the following two key techniques: (1) the well-known mean-shift algorithm, which can provide accurate and rapid CF estimation; and (2) an original two-direction-combination strategy, which can further enhance the accuracy and robustness of CF estimation. Some other available CF estimation algorithms are brought out for comparison. Several validation approaches that can work on the real data without ground truths are specially designed. Experimental results on human body in vivo cardiac data demonstrate the significance of accurate CF estimation for SinMod, and validate the effectiveness of RACE in facilitating the motion estimation performance of SinMod.
AD - School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China; Key Laboratory of Education Ministry for Image Processing and Intelligence Control, Wuhan, Hubei 430074, China.
School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China; Key Laboratory of Education Ministry for Image Processing and Intelligence Control, Wuhan, Hubei 430074, China. Electronic address: xuxy@hust.edu.cn.
Key Laboratory of Education Ministry for Image Processing and Intelligence Control, Wuhan, Hubei 430074, China; Department of Information and Safety Engineering, Zhongnan University of Economics and Law, Wuhan, Hubei 430073, China.
School of Computing and Software Engineering, Southern Polytechnic State University, Marietta, GA 30060, USA.
Quantitative BioImaging Laboratory, Emory University School of Medicine, Atlanta, GA 30322, USA.
AN - 25087857
AU - Liu, H.
AU - Wang, J.
AU - Xu, X.
AU - Song, E.
AU - Wang, Q.
AU - Jin, R.
AU - Hung, C. C.
AU - Fei, B.
DA - Nov
DO - S0730-725X(14)00208-2 [pii]
10.1016/j.mri.2014.07.005 [doi]
DP - Nlm
ET - 2014/08/05
L1 - internal-pdf://1074571960/Liu-2014-A robust and accurate center-frequenc.pdf
LA - eng
M1 - 9
N1 - Liu, Hong
Wang, Jie
Xu, Xiangyang
Song, Enmin
Wang, Qian
Jin, Renchao
Hung, Chih-Cheng
Fei, Baowei
Research Support, Non-U.S. Gov't
Netherlands
Magnetic resonance imaging
Magn Reson Imaging. 2014 Nov;32(9):1139-55. doi: 10.1016/j.mri.2014.07.005. Epub 2014 Aug 1.
PY - 2014
SN - 1873-5894 (Electronic)
0730-725X (Linking)
SP - 1139-55
ST - A robust and accurate center-frequency estimation (RACE) algorithm for improving motion estimation performance of SinMod on tagged cardiac MR images without known tagging parameters
T2 - Magn Reson Imaging
TI - A robust and accurate center-frequency estimation (RACE) algorithm for improving motion estimation performance of SinMod on tagged cardiac MR images without known tagging parameters
UR - http://ac.els-cdn.com/S0730725X14002082/1-s2.0-S0730725X14002082-main.pdf?_tid=e281ec84-c132-11e4-b38d-00000aab0f6c&acdnat=1425338682_7a3dfa04f9d9e5ad22b77553092e3266
VL - 32
ID - 244
ER -
TY - JOUR
AB - Hyperspectral imaging (HSI) is an emerging imaging modality for medical applications, especially in disease diagnosis and image-guided surgery. HSI acquires a three-dimensional dataset called hypercube, with two spatial dimensions and one spectral dimension. Spatially resolved spectral imaging obtained by HSI provides diagnostic information about the tissue physiology, morphology, and composition. This review paper presents an overview of the literature on medical hyperspectral imaging technology and its applications. The aim of the survey is threefold: an introduction for those new to the field, an overview for those working in the field, and a reference for those searching for literature on a specific application.
AD - Emory University and Georgia Institute of Technology, The Wallace H. Coulter Department of Biomedical Engineering, Atlanta, Georgia 30322.
Emory University and Georgia Institute of Technology, The Wallace H. Coulter Department of Biomedical Engineering, Atlanta, Georgia 30322bEmory University, School of Medicine, Department of Radiology and Imaging Sciences, Atlanta, Georgia 30329cEmory Univ.
AN - 24441941
AU - Lu, G.
AU - Fei, B.
C2 - 3895860
DA - Jan
DO - 1816617 [pii]
10.1117/1.JBO.19.1.010901 [doi]
DP - Nlm
ET - 2014/01/21
KW - Color
Computers
Diabetic Foot/diagnosis
Diagnostic Imaging/ trends
Fluorescent Dyes/chemistry
Heart Diseases/diagnosis
Humans
Imaging, Three-Dimensional
Light
Metals/chemistry
Neoplasms/diagnosis
Neural Networks (Computer)
Oxides/chemistry
Retinal Diseases/diagnosis
Semiconductors
Shock/diagnosis
Spectrophotometry/ methods
Support Vector Machines
Surface Properties
Surgical Procedures, Operative
L1 - internal-pdf://0170009222/Lu-2014-Medical hyperspectral imaging_ a revie.pdf
LA - eng
M1 - 1
N1 - Lu, Guolan
Fei, Baowei
Review
United States
Journal of biomedical optics
J Biomed Opt. 2014 Jan;19(1):10901. doi: 10.1117/1.JBO.19.1.010901.
PY - 2014
SN - 1560-2281 (Electronic)
1083-3668 (Linking)
SP - 10901
ST - Medical hyperspectral imaging: a review
T2 - J Biomed Opt
TI - Medical hyperspectral imaging: a review
UR - http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3895860/pdf/JBO-019-010901.pdf
VL - 19
ID - 253
ER -
TY - JOUR
AB - As an emerging technology, hyperspectral imaging (HSI) combines both the chemical specificity of spectroscopy and the spatial resolution of imaging, which may provide a non-invasive tool for cancer detection and diagnosis. Early detection of malignant lesions could improve both survival and quality of life of cancer patients. In this paper, we introduce a tensor-based computation and modeling framework for the analysis of hyperspectral images to detect head and neck cancer. The proposed classification method can distinguish between malignant tissue and healthy tissue with an average sensitivity of 96.97% and an average specificity of 91.42% in tumor-bearing mice. The hyperspectral imaging and classification technology has been demonstrated in animal models and can have many potential applications in cancer research and management.
AD - The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA.
Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA.
Department of Hematology and Medical Oncology, Emory University, Atlanta, GA.
The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA ; Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA ; Department of Mathematics & Computer Science, Emory University, Atlanta, GA ; Winship Cancer Institute of Emory University, Atlanta, GA.
AN - 25328639
AU - Lu, G.
AU - Halig, L.
AU - Wang, D.
AU - Chen, Z. G.
AU - Fei, B.
C2 - 4201059
DA - Mar 21
DO - 10.1117/12.2043796 [doi]
DP - Nlm
ET - 2014/10/21
L1 - internal-pdf://4135373603/Lu-2014-Spectral-Spatial Classification Using.pdf
LA - Eng
N1 - Lu, Guolan
Halig, Luma
Wang, Dongsheng
Chen, Zhuo Georgia
Fei, Baowei
R01 CA156775/CA/NCI NIH HHS/United States
R21 CA176684/CA/NCI NIH HHS/United States
Proceedings of SPIE
Nihms613551
Proc SPIE. 2014 Mar 21;9034:903413.
PY - 2014
SN - 1996-756X (Print)
1996-756X (Linking)
SP - 903413
ST - Spectral-Spatial Classification Using Tensor Modeling for Cancer Detection with Hyperspectral Imaging
T2 - Proc SPIE
TI - Spectral-Spatial Classification Using Tensor Modeling for Cancer Detection with Hyperspectral Imaging
UR - http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4201059/pdf/nihms-613551.pdf
VL - 9034
ID - 250
ER -
TY - JOUR
AB - The determination of tumor margins during surgical resection remains a challenging task. A complete removal of malignant tissue and conservation of healthy tissue is important for the preservation of organ function, patient satisfaction, and quality of life. Visual inspection and palpation is not sufficient for discriminating between malignant and normal tissue types. Hyperspectral imaging (HSI) technology has the potential to noninvasively delineate surgical tumor margin and can be used as an intra-operative visual aid tool. Since histological images provide the ground truth of cancer margins, it is necessary to warp the cancer regions in ex vivo histological images back to in vivo hyperspectral images in order to validate the tumor margins detected by HSI and to optimize the imaging parameters. In this paper, principal component analysis (PCA) is utilized to extract the principle component bands of the HSI images, which is then used to register HSI images with the corresponding histological image. Affine registration is chosen to model the global transformation. A B-spline free form deformation (FFD) method is used to model the local non-rigid deformation. Registration experiment was performed on animal hyperspectral and histological images. Experimental results from animals demonstrated the feasibility of the hyperspectral imaging method for cancer margin detection.
AD - The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA.
Department of Hematology and Medical Oncology, Emory University, Atlanta, GA.
The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA ; Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA ; Department of Mathematics & Computer Science, Emory University, Atlanta, GA ; Winship Cancer Institute of Emory University, Atlanta, GA.
AN - 25328640
AU - Lu, G.
AU - Halig, L.
AU - Wang, D.
AU - Chen, Z. G.
AU - Fei, B.
C2 - 4201054
DA - Mar 12
DO - 10.1117/12.2043805 [doi]
DP - Nlm
ET - 2014/10/21
L1 - internal-pdf://1579346066/Lu-2014-Hyperspectral Imaging for Cancer Surgi.pdf
LA - Eng
N1 - Lu, Guolan
Halig, Luma
Wang, Dongsheng
Chen, Zhuo Georgia
Fei, Baowei
R01 CA156775/CA/NCI NIH HHS/United States
R21 CA176684/CA/NCI NIH HHS/United States
Proceedings of SPIE
Nihms613556
Proc SPIE. 2014 Mar 12;9036:90360S.
PY - 2014
SN - 1996-756X (Print)
1996-756X (Linking)
SP - 90360S
ST - Hyperspectral Imaging for Cancer Surgical Margin Delineation: Registration of Hyperspectral and Histological Images
T2 - Proc SPIE
TI - Hyperspectral Imaging for Cancer Surgical Margin Delineation: Registration of Hyperspectral and Histological Images
UR - http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4201054/pdf/nihms613556.pdf
VL - 9036
ID - 252
ER -
TY - JOUR
AB - Early detection of malignant lesions could improve both survival and quality of life of cancer patients. Hyperspectral imaging (HSI) has emerged as a powerful tool for noninvasive cancer detection and diagnosis, with the advantage of avoiding tissue biopsy and providing diagnostic signatures without the need of a contrast agent in real time. We developed a spectral-spatial classification method to distinguish cancer from normal tissue on hyperspectral images. We acquire hyperspectral reflectance images from 450 to 900 nm with a 2-nm increment from tumor-bearing mice. In our animal experiments, the HSI and classification method achieved a sensitivity of 93.7% and a specificity of 91.3%. The preliminary study demonstrated that HSI has the potential to be applied in vivo for noninvasive detection of tumors.
AD - Georgia Institute of Technology and Emory University, The Wallace H. Coulter Department of Biomedical Engineering, Atlanta, Georgia 30329, United States.
Emory University School of Medicine, Department of Radiology and Imaging Sciences, Atlanta, Georgia 30329, United States.
Emory University School of Medicine, Department of Hematology and Medical Oncology, Atlanta, Georgia 30329, United States.
Georgia Institute of Technology and Emory University, The Wallace H. Coulter Department of Biomedical Engineering, Atlanta, Georgia 30329, United StatesbEmory University School of Medicine, Department of Radiology and Imaging Sciences, Atlanta, Georgia 30.
AN - 25277147
AU - Lu, G.
AU - Halig, L.
AU - Wang, D.
AU - Qin, X.
AU - Chen, Z. G.
AU - Fei, B.
C2 - 4183763
DA - Oct
DO - 1915159 [pii]
10.1117/1.JBO.19.10.106004 [doi]
DP - Nlm
ET - 2014/10/04
LA - eng
M1 - 10
N1 - Lu, Guolan
Halig, Luma
Wang, Dongsheng
Qin, Xulei
Chen, Zhuo Georgia
Fei, Baowei
P50CA128301/CA/NCI NIH HHS/United States
P50CA128613/CA/NCI NIH HHS/United States
R01CA156775/CA/NCI NIH HHS/United States
R21CA176684/CA/NCI NIH HHS/United States
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
United States
Journal of biomedical optics
J Biomed Opt. 2014 Oct;19(10):106004. doi: 10.1117/1.JBO.19.10.106004.
PY - 2014
SN - 1560-2281 (Electronic)
1083-3668 (Linking)
SP - 106004
ST - Spectral-spatial classification for noninvasive cancer detection using hyperspectral imaging
T2 - J Biomed Opt
TI - Spectral-spatial classification for noninvasive cancer detection using hyperspectral imaging
UR - http://biomedicaloptics.spiedigitallibrary.org/article.aspx?articleid=1915159
VL - 19
ID - 245
ER -
TY - JOUR
AB - The aim of this study is to investigate the impact on image quality of using monochromatic beams for lower dose breast tomosynthesis (BT). For this purpose, modeling and simulation of BT and mammography imaging processes have been performed using two x-ray beams: one at 28 kVp and a monochromatic one at 19 keV at different entrance surface air kerma ranging between 0.16 and 5.5 mGy. Two 4 cm thick computational breast models, in a compressed state, were used: one simple homogeneous and one heterogeneous based on CT breast images, with compositions of 50% glandular-50% adipose and 40% glandular-60% adipose tissues by weight, respectively. Modeled lesions, representing masses and calcifications, were inserted within these breast phantoms. X-ray transport in the breast models was simulated with previously developed and validated Monte Carlo application. Results showed that, for the same incident photon fluence, the use of the monochromatic beam in BT resulted in higher image quality compared to the one using polychromatic acquisition, especially in terms of contrast. For the homogenous phantom, the improvement ranged between 15% and 22% for calcifications and masses, respectively, while for the heterogeneous one this improvement was in the order of 33% for the masses and 17% for the calcifications. For different exposures, comparable image quality in terms of signal-difference-to-noise ratio and higher contrast for all features was obtained when using a monochromatic 19 keV beam at a lower mean glandular dose, compared to the polychromatic one. Monochromatic images also provide better detail and, in combination with BT, can lead to substantial improvement in visualization of features, and particularly better edge detection of low-contrast masses.
AD - Department of Medical Physics, Faculty of Medicine, University of Patras, Patras 26500, Greece.
AN - 25082791
AU - Malliori, A.
AU - Bliznakova, K.
AU - Sechopoulos, I.
AU - Kamarianakis, Z.
AU - Fei, B.
AU - Pallikarakis, N.
C2 - 4164851
DA - Aug 21
DO - 10.1088/0031-9155/59/16/4681 [doi]
DP - Nlm
ET - 2014/08/02
LA - eng
M1 - 16
N1 - Malliori, A
Bliznakova, K
Sechopoulos, I
Kamarianakis, Z
Fei, B
Pallikarakis, N
R01 CA156775/CA/NCI NIH HHS/United States
R01 CA163746/CA/NCI NIH HHS/United States
R01CA156775/CA/NCI NIH HHS/United States
R01CA163746/CA/NCI NIH HHS/United States
R21 CA176684/CA/NCI NIH HHS/United States
R21CA176684/CA/NCI NIH HHS/United States
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
England
Physics in medicine and biology
Nihms619064
Phys Med Biol. 2014 Aug 21;59(16):4681-96. doi: 10.1088/0031-9155/59/16/4681. Epub 2014 Aug 1.
PY - 2014
SN - 1361-6560 (Electronic)
0031-9155 (Linking)
SP - 4681-96
ST - Breast tomosynthesis with monochromatic beams: a feasibility study using Monte Carlo simulations
T2 - Phys Med Biol
TI - Breast tomosynthesis with monochromatic beams: a feasibility study using Monte Carlo simulations
UR - http://iopscience.iop.org/0031-9155/59/16/4681/
VL - 59
ID - 246
ER -
TY - JOUR
AB - Hyperspectral imaging is a developing modality for cancer detection. The rich information associated with hyperspectral images allow for the examination between cancerous and healthy tissue. This study focuses on a new method that incorporates support vector machines into a minimum spanning forest algorithm for differentiating cancerous tissue from normal tissue. Spectral information was gathered to test the algorithm. Animal experiments were performed and hyperspectral images were acquired from tumor-bearing mice. In vivo imaging experimental results demonstrate the applicability of the proposed classification method for cancer tissue classification on hyperspectral images.
AD - Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA.
The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA.
Department of Hematology and Medical Oncology, Emory University, Atlanta, GA.
Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA ; The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA ; Department of Mathematics & Computer Science, Emory University, Atlanta, GA ; Winship Cancer Institute of Emory University, Atlanta, GA.
AN - 25426272
AU - Pike, R.
AU - Patton, S. K.
AU - Lu, G.
AU - Halig, L. V.
AU - Wang, D.
AU - Chen, Z. G.
AU - Fei, B.
C2 - 4241346
DA - Mar 21
DO - 10.1117/12.2043848 [doi]
DP - Nlm
ET - 2014/11/27
L1 - internal-pdf://2592798436/Pike-2014-A Minimum Spanning Forest Based Hype.pdf
LA - Eng
N1 - Pike, Robert
Patton, Samuel K
Lu, Guolan
Halig, Luma V
Wang, Dongsheng
Chen, Zhuo Georgia
Fei, Baowei
R01 CA156775/CA/NCI NIH HHS/United States
R21 CA176684/CA/NCI NIH HHS/United States
Proceedings of SPIE
Nihms613555
Proc SPIE. 2014 Mar 21;9034:90341W.
PY - 2014
SN - 1996-756X (Print)
1996-756X (Linking)
SP - 90341W
ST - A Minimum Spanning Forest Based Hyperspectral Image Classification Method for Cancerous Tissue Detection
T2 - Proc SPIE
TI - A Minimum Spanning Forest Based Hyperspectral Image Classification Method for Cancerous Tissue Detection
UR - http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4241346/pdf/nihms613555.pdf
VL - 9034
ID - 248
ER -
TY - JOUR
AB - High-frequency ultrasound (HFU) has the ability to image both skeletal and cardiac muscles. The quantitative assessment of these myofiber orientations has a number of applications in both research and clinical examinations; however, difficulties arise due to the severe speckle noise contained in the HFU images. Thus, for the purpose of automatically measuring myofiber orientations from two-dimensional HFU images, we propose a two-step multiscale image decomposition method. It combines a nonlinear anisotropic diffusion filter and a coherence enhancing diffusion filter to extract myofibers. This method has been verified by ultrasound data from simulated phantoms, excised fiber phantoms, specimens of porcine hearts, and human skeletal muscles in vivo. The quantitative evaluations of both phantoms indicated that the myofiber measurements of our proposed method were more accurate than other methods. The myofiber orientations extracted from different layers of the porcine hearts matched the prediction of an established cardiac mode and demonstrated the feasibility of extracting cardiac myofiber orientations from HFU images ex vivo. Moreover, HFU also demonstrated the ability to measure myofiber orientations in vivo.
AD - Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA 30329, USA.
AN - 24957945
AU - Qin, X.
AU - Fei, B.
C2 - 4137038
DA - Jul 21
DO - 10.1088/0031-9155/59/14/3907 [doi]
DP - Nlm
ET - 2014/06/25
KW - Animals
Echocardiography/ methods
Heart Ventricles/cytology
Humans
Image Processing, Computer-Assisted/ methods
Myocardium/ cytology
Phantoms, Imaging
Swine
LA - eng
M1 - 14
N1 - Qin, Xulei
Fei, Baowei
P50CA128301/CA/NCI NIH HHS/United States
R01 CA156775/CA/NCI NIH HHS/United States
R01CA156775/CA/NCI NIH HHS/United States
R21 CA120536/CA/NCI NIH HHS/United States
R21 CA176684/CA/NCI NIH HHS/United States
R21CA176684/CA/NCI NIH HHS/United States
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
England
Physics in medicine and biology
Nihms610547
Phys Med Biol. 2014 Jul 21;59(14):3907-24. doi: 10.1088/0031-9155/59/14/3907. Epub 2014 Jun 24.
PY - 2014
SN - 1361-6560 (Electronic)
0031-9155 (Linking)
SP - 3907-24
ST - Measuring myofiber orientations from high-frequency ultrasound images using multiscale decompositions
T2 - Phys Med Biol
TI - Measuring myofiber orientations from high-frequency ultrasound images using multiscale decompositions
UR - http://iopscience.iop.org/0031-9155/59/14/3907/
VL - 59
ID - 247
ER -
TY - JOUR
AB - Digital breast tomosynthesis (DBT) is a pseudo-three-dimensional x-ray imaging modality proposed to decrease the effect of tissue superposition present in mammography, potentially resulting in an increase in clinical performance for the detection and diagnosis of breast cancer. Tissue classification in DBT images can be useful in risk assessment, computer-aided detection and radiation dosimetry, among other aspects. However, classifying breast tissue in DBT is a challenging problem because DBT images include complicated structures, image noise, and out-of-plane artifacts due to limited angular tomographic sampling. In this project, we propose an automatic method to classify fatty and glandular tissue in DBT images. First, the DBT images are pre-processed to enhance the tissue structures and to decrease image noise and artifacts. Second, a global smooth filter based on L0 gradient minimization is applied to eliminate detailed structures and enhance large-scale ones. Third, the similar structure regions are extracted and labeled by fuzzy C-means (FCM) classification. At the same time, the texture features are also calculated. Finally, each region is classified into different tissue types based on both intensity and texture features. The proposed method is validated using five patient DBT images using manual segmentation as the gold standard. The Dice scores and the confusion matrix are utilized to evaluate the classified results. The evaluation results demonstrated the feasibility of the proposed method for classifying breast glandular and fat tissue on DBT images.
AD - Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA.
Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA.
Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA ; Winship Cancer Institute, Emory University, Atlanta, GA.
Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA ; Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA ; Department of Mathematics & Computer Science, Emory University, Atlanta, GA ; Winship Cancer Institute, Emory University, Atlanta, GA.
AN - 25426271
AU - Qin, X.
AU - Lu, G.
AU - Sechopoulos, I.
AU - Fei, B.
C2 - 4241347
DA - Mar 21
DO - 10.1117/12.2043828 [doi]
DP - Nlm
ET - 2014/11/27
L1 - internal-pdf://2912072574/Qin-2014-Breast Tissue Classification in Digit.pdf
LA - Eng
N1 - Qin, Xulei
Lu, Guolan
Sechopoulos, Ioannis
Fei, Baowei
R01 CA156775/CA/NCI NIH HHS/United States
R21 CA176684/CA/NCI NIH HHS/United States
Proceedings of SPIE
Nihms613554
Proc SPIE. 2014 Mar 21;9034:90341V.
PY - 2014
SN - 1996-756X (Print)
1996-756X (Linking)
SP - 90341V
ST - Breast Tissue Classification in Digital Tomosynthesis Images Based on Global Gradient Minimization and Texture Features
T2 - Proc SPIE
TI - Breast Tissue Classification in Digital Tomosynthesis Images Based on Global Gradient Minimization and Texture Features
UR - http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4241347/pdf/nihms613554.pdf
VL - 9034
ID - 249
ER -
TY - JOUR
AB - The orientation of cardiac fibers affects the anatomical, mechanical, and electrophysiological properties of the heart. Although echocardiography is the most common imaging modality in clinical cardiac examination, it can only provide the cardiac geometry or motion information without cardiac fiber orientations. If the patient's cardiac fiber orientations can be mapped to his/her echocardiography images in clinical examinations, it may provide quantitative measures for diagnosis, personalized modeling, and image-guided cardiac therapies. Therefore, this project addresses the feasibility of mapping personalized cardiac fiber orientations to three-dimensional (3D) ultrasound image volumes. First, the geometry of the heart extracted from the MRI is translated to 3D ultrasound by rigid and deformable registration. Deformation fields between both geometries from MRI and ultrasound are obtained after registration. Three different deformable registration methods were utilized for the MRI-ultrasound registration. Finally, the cardiac fiber orientations imaged by DTI are mapped to ultrasound volumes based on the extracted deformation fields. Moreover, this study also demonstrated the ability to simulate electricity activations during the cardiac resynchronization therapy (CRT) process. The proposed method has been validated in two rat hearts and three canine hearts. After MRI/ultrasound image registration, the Dice similarity scores were more than 90% and the corresponding target errors were less than 0.25 mm. This proposed approach can provide cardiac fiber orientations to ultrasound images and can have a variety of potential applications in cardiac imaging.
AD - Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA.
Yerkes National Primate Research Center, Emory University, Atlanta, GA.
Department of Pediatrics, Emory University, Atlanta, GA.
Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA ; Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA.
AN - 25328641
AU - Qin, X.
AU - Wang, S.
AU - Shen, M.
AU - Zhang, X.
AU - Wagner, M. B.
AU - Fei, B.
C2 - 4201058
DA - Mar 12
DO - 10.1117/12.2043821 [doi]
DP - Nlm
ET - 2014/10/21
L1 - internal-pdf://3083131269/Qin-2014-Mapping Cardiac Fiber Orientations fr.pdf
LA - Eng
N1 - Qin, Xulei
Wang, Silun
Shen, Ming
Zhang, Xiaodong
Wagner, Mary B
Fei, Baowei
R01 CA156775/CA/NCI NIH HHS/United States
R21 CA176684/CA/NCI NIH HHS/United States
Proceedings of SPIE
Nihms613557
Proc SPIE. 2014 Mar 12;9036:90361O.
PY - 2014
SN - 1996-756X (Print)
1996-756X (Linking)
SP - 90361O
ST - Mapping Cardiac Fiber Orientations from High-Resolution DTI to High-Frequency 3D Ultrasound
T2 - Proc SPIE
TI - Mapping Cardiac Fiber Orientations from High-Resolution DTI to High-Frequency 3D Ultrasound
UR - http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4201058/pdf/nihms613557.pdf
VL - 9036
ID - 251
ER -