@article{ author = {Akbari, H. and Fei, B.}, title = {3D ultrasound image segmentation using wavelet support vector machines}, journal = {Med Phys}, volume = {39}, number = {6}, pages = {2972-84}, note = {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.}, abstract = {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.}, keywords = {Humans Imaging, Three-Dimensional/ methods Male Prostate/ultrasonography Support Vector Machines Ultrasonography/ methods}, ISSN = {0094-2405 (Print) 0094-2405 (Linking)}, DOI = {10.1118/1.4709607 [doi]}, url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3360689/pdf/MPHYA6-000039-002972_1.pdf}, year = {2012}, type = {Journal Article} } @article{ author = {Akbari, H. and Fei, B.}, title = {Automatic 3D Segmentation of the Kidney in MR Images Using Wavelet Feature Extraction and Probability Shape Model}, journal = {Proc SPIE}, volume = {8314}, pages = {83143D}, note = {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.}, abstract = {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.}, ISSN = {1996-756X (Print) 1996-756X (Linking)}, DOI = {10.1117/12.912028 [doi]}, url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3766988/pdf/nihms-362797.pdf}, year = {2013}, type = {Journal Article} } @article{ author = {Akbari, H. and Halig, L. V. and Schuster, D. M. and Osunkoya, A. and Master, V. and Nieh, P. T. and Chen, G. Z. and Fei, B.}, title = {Hyperspectral imaging and quantitative analysis for prostate cancer detection}, journal = {J Biomed Opt}, volume = {17}, number = {7}, pages = {076005}, note = {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.}, abstract = {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.}, keywords = {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}, ISSN = {1560-2281 (Electronic) 1083-3668 (Linking)}, DOI = {10.1117/1.JBO.17.7.076005 [doi]}, url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3608529/pdf/JBO-017-076005.pdf}, year = {2012}, type = {Journal Article} } @article{ author = {Akbari, H. and Halig, L. V. and Zhang, H. and Wang, D. and Chen, Z. G. and Fei, B.}, title = {Detection of Cancer Metastasis Using a Novel Macroscopic Hyperspectral Method}, journal = {Proc SPIE}, volume = {8317}, pages = {831711}, note = {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.}, abstract = {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.}, ISSN = {1996-756X (Print) 1996-756X (Linking)}, DOI = {10.1117/12.912026 [doi]}, url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3546351/pdf/nihms432042.pdf}, year = {2012}, type = {Journal Article} } @article{ author = {Akbari, H. and Yang, X. and Halig, L. V. and Fei, B.}, title = {3D Segmentation of Prostate Ultrasound images Using Wavelet Transform}, journal = {Proc SPIE}, volume = {7962}, pages = {79622K}, note = {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.}, abstract = {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.}, ISSN = {1996-756X (Print) 1996-756X (Linking)}, DOI = {10.1117/12.878072 [doi]}, url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3314427/pdf/nihms362788.pdf}, year = {2011}, type = {Journal Article} } @article{ author = {Bebek, O. and Hwang, M. J. and Fei, B. and Cavusoglu, M.}, title = {Design of a small animal biopsy robot}, journal = {Conf Proc IEEE Eng Med Biol Soc}, volume = {2008}, pages = {5601-4}, note = {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.}, abstract = {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.}, keywords = {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}, ISSN = {1557-170X (Print) 1557-170X (Linking)}, DOI = {10.1109/IEMBS.2008.4650484 [doi]}, url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2796956/pdf/nihms113528.pdf}, year = {2008}, type = {Journal Article} } @article{ author = {Bogie, K. and Wang, X. and Fei, B. and Sun, J.}, title = {New technique for real-time interface pressure analysis: getting more out of large image data sets}, journal = {J Rehabil Res Dev}, volume = {45}, number = {4}, pages = {523-35, 10 p following 535}, note = {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.}, abstract = {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.}, keywords = {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}, ISSN = {1938-1352 (Electronic) 0748-7711 (Linking)}, year = {2008}, type = {Journal Article} } @article{ author = {Chen, X. and Gilkeson, R. and Fei, B.}, title = {Automatic Intensity-based 3D-to-2D Registration of CT Volume and Dual-energy Digital Radiography for the Detection of Cardiac Calcification}, journal = {Proc SPIE}, volume = {6512}, note = {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.}, abstract = {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.}, ISSN = {1996-756X (Print) 1996-756X (Linking)}, DOI = {10.1117/12.710192 [doi]}, url = {http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=1336654}, year = {2007}, type = {Journal Article} } @article{ author = {Chen, X. and Gilkeson, R. C. and Fei, B.}, title = {Automatic 3D-to-2D registration for CT and dual-energy digital radiography for calcification detection}, journal = {Med Phys}, volume = {34}, number = {12}, pages = {4934-43}, note = {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.}, abstract = {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.}, keywords = {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}, ISSN = {0094-2405 (Print) 0094-2405 (Linking)}, url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2743028/pdf/nihms113518.pdf}, year = {2007}, type = {Journal Article} } @article{ author = {Chen, X. and Li, K. and Gilkeson, R. and Fei, B.}, title = {Gaussian Weighted Projection for Visualization of Cardiac Calcification}, journal = {Proc SPIE}, volume = {6918}, note = {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.}, abstract = {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.}, ISSN = {1996-756X (Print) 1996-756X (Linking)}, DOI = {10.1117/12.772597 [doi]}, url = {http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=829872}, year = {2008}, type = {Journal Article} } @article{ author = {Cheng, Y. and A, C. Samia and Meyers, J. D. and Panagopoulos, I. and Fei, B. and Burda, C.}, title = {Highly efficient drug delivery with gold nanoparticle vectors for in vivo photodynamic therapy of cancer}, journal = {J Am Chem Soc}, volume = {130}, number = {32}, pages = {10643-7}, note = {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.}, abstract = {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.}, keywords = {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}, ISSN = {1520-5126 (Electronic) 0002-7863 (Linking)}, DOI = {10.1021/ja801631c [doi]}, url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2719258/pdf/nihms-113517.pdf}, year = {2008}, type = {Journal Article} } @article{ author = {Fei, B. and Chen, X. and Wang, H. and Sabol, J. M. and DuPont, E. and Gilkeson, R. C.}, title = {Automatic registration of CT volumes and dual-energy digital radiography for detection of cardiac and lung diseases}, journal = {Conf Proc IEEE Eng Med Biol Soc}, volume = {1}, pages = {1976-9}, note = {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.}, abstract = {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.}, keywords = {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}, ISSN = {1557-170X (Print) 1557-170X (Linking)}, DOI = {10.1109/IEMBS.2006.259888 [doi]}, url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2743908/pdf/nihms-113523.pdf}, year = {2006}, type = {Journal Article} } @article{ author = {Fei, B. and Duerk, J. L. and Boll, D. T. and Lewin, J. S. and Wilson, D. L.}, title = {Slice-to-volume registration and its potential application to interventional MRI-guided radio-frequency thermal ablation of prostate cancer}, journal = {IEEE Trans Med Imaging}, volume = {22}, number = {4}, pages = {515-25}, note = {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.}, abstract = {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.}, keywords = {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}, ISSN = {0278-0062 (Print) 0278-0062 (Linking)}, DOI = {10.1109/TMI.2003.809078 [doi]}, url = {http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=1200925}, year = {2003}, type = {Journal Article} } @article{ author = {Fei, B. and Duerk, J. L. and Sodee, D. B. and Wilson, D. L.}, title = {Semiautomatic nonrigid registration for the prostate and pelvic MR volumes}, journal = {Acad Radiol}, volume = {12}, number = {7}, pages = {815-24}, note = {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.}, abstract = {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.}, keywords = {Algorithms Femur/pathology Humans Imaging, Three-Dimensional Magnetic Resonance Imaging/ methods Male Pelvis/ pathology Prostatic Neoplasms/ pathology/therapy}, ISSN = {1076-6332 (Print) 1076-6332 (Linking)}, DOI = {S1076-6332(05)00277-1 [pii] 10.1016/j.acra.2005.03.063 [doi]}, url = {http://ac.els-cdn.com/S1076633205002771/1-s2.0-S1076633205002771-main.pdf?_tid=3ef685f6-c133-11e4-a312-00000aab0f01&acdnat=1425338837_8552b62667aa34e1d8727734539b9434}, year = {2005}, type = {Journal Article} } @article{ author = {Fei, B. and Duerk, J. L. and Wilson, D. L.}, title = {Automatic 3D registration for interventional MRI-guided treatment of prostate cancer}, journal = {Comput Aided Surg}, volume = {7}, number = {5}, pages = {257-67}, note = {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.}, abstract = {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.}, keywords = {Algorithms Computer Simulation Feasibility Studies Humans Imaging, Three-Dimensional/ methods Magnetic Resonance Imaging/ methods Male Minimally Invasive Surgical Procedures Prostatic Neoplasms/ pathology}, ISSN = {1092-9088 (Print) 1092-9088 (Linking)}, DOI = {10.1002/igs.10052 [doi]}, url = {http://informahealthcare.com/doi/pdfplus/10.3109/10929080209146034}, year = {2002}, type = {Journal Article} } @article{ author = {Fei, B. and Flask, C. and Wang, H. and Pi, A. and Wilson, D. and Shillingford, J. and Murcia, N. and Weimbs, T. and Duerk, J.}, title = {Image Segmentation, Registration and Visualization of Serial MR Images for Therapeutic Assessment of Polycystic Kidney Disease in Transgenic Mice}, journal = {Conf Proc IEEE Eng Med Biol Soc}, volume = {1}, pages = {467-9}, note = {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.}, abstract = {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.}, ISSN = {1557-170X (Print) 1557-170X (Linking)}, DOI = {10.1109/IEMBS.2005.1616448 [doi]}, url = {http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=1616448}, year = {2005}, type = {Journal Article} } @article{ author = {Fei, B. and Kemper, C. and Wilson, D. L.}, title = {A comparative study of warping and rigid body registration for the prostate and pelvic MR volumes}, journal = {Comput Med Imaging Graph}, volume = {27}, number = {4}, pages = {267-81}, note = {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.}, abstract = {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.}, keywords = {Algorithms Humans Imaging, Three-Dimensional Magnetic Resonance Imaging/ methods Male Models, Statistical Pelvis/ pathology Posture Prostate/ pathology Prostatic Neoplasms/ therapy Radiometry/ methods}, ISSN = {0895-6111 (Print) 0895-6111 (Linking)}, DOI = {S0895611102000939 [pii]}, url = {http://ac.els-cdn.com/S0895611102000939/1-s2.0-S0895611102000939-main.pdf?_tid=425432c0-c133-11e4-95be-00000aacb362&acdnat=1425338842_3c4972d7c33914de94ffff1125de8a32}, year = {2003}, type = {Journal Article} } @article{ author = {Fei, B. and Nieh, P. T. and Schuster, D. M. and Master, V. A.}, title = {PET-directed, 3D Ultrasound-guided prostate biopsy}, journal = {Diagn Imaging Eur}, volume = {29}, number = {1}, pages = {12-15}, note = {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.}, abstract = {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.}, ISSN = {1461-0051 (Print) 1461-0051 (Linking)}, url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4225556/pdf/nihms514152.pdf}, year = {2013}, type = {Journal Article} } @article{ author = {Fei, B. and Schuster, D. M. and Master, V. and Akbari, H. and Fenster, A. and Nieh, P.}, title = {A Molecular Image-directed, 3D Ultrasound-guided Biopsy System for the Prostate}, journal = {Proc SPIE}, volume = {2012}, note = {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.}, abstract = {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.}, ISSN = {1996-756X (Print) 1996-756X (Linking)}, DOI = {10.1117/12.912182 [doi]}, url = {http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=1346064}, year = {2012}, type = {Journal Article} } @article{ author = {Fei, B. and Suri, J. S. and Wilson, D. L.}, title = {Three-Dimensional Volume Registration of Carotid MR Images}, journal = {Stud Health Technol Inform}, volume = {113}, pages = {394-411}, note = {Fei, Baowei Suri, Jasjit S Wilson, David L Netherlands Studies in health technology and informatics Stud Health Technol Inform. 2005;113:394-411.}, abstract = {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.}, ISSN = {0926-9630 (Print) 0926-9630 (Linking)}, year = {2005}, type = {Journal Article} } @article{ author = {Fei, B. and Wang, H. and Chen, X. and Meyers, J. and Mulvihill, J. and Feyes, D. and Edgehouse, N. and Duerk, J. L. and Pretlow, T. G. and Oleinick, N. L.}, title = {Small Animal Imaging for Early Assessment of Therapeutic Efficacy of Photodynamic Therapy for Prostate Cancer}, journal = {Proc SPIE}, volume = {6511}, note = {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.}, abstract = {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.}, ISSN = {1996-756X (Print) 1996-756X (Linking)}, DOI = {10.1117/12.708718 [doi]}, url = {http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=1336638}, year = {2007}, type = {Journal Article} } @article{ author = {Fei, B. and Wang, H. and Meyers, J. D. and Feyes, D. K. and Oleinick, N. L. and Duerk, J. L.}, title = {High-field magnetic resonance imaging of the response of human prostate cancer to Pc 4-based photodynamic therapy in an animal model}, journal = {Lasers Surg Med}, volume = {39}, number = {9}, pages = {723-30}, note = {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.}, abstract = {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.}, keywords = {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}, ISSN = {0196-8092 (Print) 0196-8092 (Linking)}, DOI = {10.1002/lsm.20576 [doi]}, url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2719260/pdf/nihms-113521.pdf}, year = {2007}, type = {Journal Article} } @article{ author = {Fei, B. and Wang, H. and Muzic, R. F., Jr. and Flask, C. and Wilson, D. L. and Duerk, J. L. and Feyes, D. K. and Oleinick, N. L.}, title = {Deformable and rigid registration of MRI and microPET images for photodynamic therapy of cancer in mice}, journal = {Med Phys}, volume = {33}, number = {3}, pages = {753-60}, note = {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.}, abstract = {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.}, keywords = {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}, ISSN = {0094-2405 (Print) 0094-2405 (Linking)}, year = {2006}, type = {Journal Article} } @article{ author = {Fei, B. and Wang, H. and Wu, C. and Chiu, S. M.}, title = {Choline PET for monitoring early tumor response to photodynamic therapy}, journal = {J Nucl Med}, volume = {51}, number = {1}, pages = {130-8}, note = {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.}, abstract = {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.}, keywords = {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}, ISSN = {1535-5667 (Electronic) 0161-5505 (Linking)}, DOI = {jnumed.109.067579 [pii] 10.2967/jnumed.109.067579 [doi]}, url = {http://jnm.snmjournals.org/content/51/1/130.full.pdf}, year = {2010}, type = {Journal Article} } @article{ author = {Fei, B. and Wang, H. and Wu, C. and Meyers, J. and Xue, L. Y. and Maclennan, G. and Schluchter, M.}, title = {Choline Molecular Imaging with Small-animal PET for Monitoring Tumor Cellular Response to Photodynamic Therapy of Cancer}, journal = {Proc SPIE}, volume = {7262}, pages = {726211}, note = {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.}, abstract = {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.}, ISSN = {1996-756X (Print) 1996-756X (Linking)}, DOI = {10.1117/12.812129 [doi]}, url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3546344/pdf/nihms432050.pdf}, year = {2009}, type = {Journal Article} } @article{ author = {Fei, B. and Wheaton, A. and Lee, Z. and Duerk, J. L. and Wilson, D. L.}, title = {Automatic MR volume registration and its evaluation for the pelvis and prostate}, journal = {Phys Med Biol}, volume = {47}, number = {5}, pages = {823-38}, note = {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.}, abstract = {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.}, keywords = {Algorithms Humans Magnetic Resonance Imaging/ methods Male Models, Statistical Pelvis/ pathology Prostate/ pathology Prostatic Neoplasms/ therapy Radiometry/ methods}, ISSN = {0031-9155 (Print) 0031-9155 (Linking)}, url = {http://iopscience.iop.org/0031-9155/47/5/309/}, year = {2002}, type = {Journal Article} } @article{ author = {Fei, B. and Yang, X. and Nye, J. A. and Aarsvold, J. N. and Raghunath, N. and Cervo, M. and Stark, R. and Meltzer, C. C. and Votaw, J. R.}, title = {MRPET quantification tools: registration, segmentation, classification, and MR-based attenuation correction}, journal = {Med Phys}, volume = {39}, number = {10}, pages = {6443-54}, note = {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.}, abstract = {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.}, keywords = {Algorithms Humans Image Processing, Computer-Assisted/ methods Magnetic Resonance Imaging/ methods Phantoms, Imaging Positron-Emission Tomography/ methods}, ISSN = {0094-2405 (Print) 0094-2405 (Linking)}, DOI = {10.1118/1.4754796 [doi]}, url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3477199/pdf/MPHYA6-000039-006443_1.pdf}, year = {2012}, type = {Journal Article} } @article{ author = {Fei, B. and Yang, X. and Wang, H.}, title = {An MRI-based Attenuation Correction Method for Combined PET/MRI Applications}, journal = {Proc SPIE}, volume = {7262}, note = {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.}, abstract = {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.}, ISSN = {1996-756X (Print) 1996-756X (Linking)}, DOI = {10.1117/12.813755 [doi]}, url = {http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=815881}, year = {2009}, type = {Journal Article} } @article{ author = {Fei, B. and Zhuang, T.}, title = {[The study of a frameless stereotactic localization method using DSA]}, journal = {Zhongguo Yi Liao Qi Xie Za Zhi}, volume = {21}, number = {4}, pages = {207-10}, note = {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.}, abstract = {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.}, keywords = {Algorithms Angiography, Digital Subtraction/ instrumentation Computer Simulation Stereotaxic Techniques}, ISSN = {1671-7104 (Print) 1671-7104 (Linking)}, year = {1997}, type = {Journal Article} } @article{ author = {Fei, B. and Zhuang, T.}, title = {[The method and development of computer-assisted surgery]}, journal = {Sheng Wu Yi Xue Gong Cheng Xue Za Zhi}, volume = {15}, number = {2}, pages = {195-202}, note = {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.}, abstract = {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.}, keywords = {General Surgery/methods Image Processing, Computer-Assisted Robotics Therapy, Computer-Assisted/methods}, ISSN = {1001-5515 (Print) 1001-5515 (Linking)}, year = {1998}, type = {Journal Article} } @article{ author = {Forouzandeh, F. and Salazar, G. and Patrushev, N. and Xiong, S. and Hilenski, L. and Fei, B. and Alexander, R. W.}, title = {Metformin beyond diabetes: pleiotropic benefits of metformin in attenuation of atherosclerosis}, journal = {J Am Heart Assoc}, volume = {3}, number = {6}, pages = {e001202}, note = {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.}, abstract = {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.}, ISSN = {2047-9980 (Electronic) 2047-9980 (Linking)}, DOI = {jah3786 [pii] 10.1161/JAHA.114.001202 [doi]}, url = {http://jaha.ahajournals.org/content/3/6/e001202.full.pdf}, year = {2014}, type = {Journal Article} } @article{ author = {Guo, S. and Fei, B.}, title = {A Minimal Path Searching Approach for Active Shape Model (ASM)-based Segmentation of the Lung}, journal = {Proc SPIE}, volume = {7259}, note = {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.}, abstract = {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.}, ISSN = {1996-756X (Print) 1996-756X (Linking)}, DOI = {10.1117/12.812575 [doi]}, url = {http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=1335511}, year = {2009}, type = {Journal Article} } @article{ author = {Haaga, J. R. and Exner, A. and Fei, B. and Seftel, A.}, title = {Semiquantitative imaging measurement of baseline and vasomodulated normal prostatic blood flow using sildenafil}, journal = {Int J Impot Res}, volume = {19}, number = {1}, pages = {110-3}, note = {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.}, abstract = {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.}, keywords = {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}, ISSN = {0955-9930 (Print) 0955-9930 (Linking)}, DOI = {3901486 [pii] 10.1038/sj.ijir.3901486 [doi]}, url = {http://www.nature.com/ijir/journal/v19/n1/pdf/3901486a.pdf}, year = {2007}, type = {Journal Article} } @article{ author = {Halig, L. V. and Wang, D. and Wang, A. Y. and Chen, Z. G. and Fei, B.}, title = {Biodistribution Study of Nanoparticle Encapsulated Photodynamic Therapy Drugs Using Multispectral Imaging}, journal = {Proc SPIE}, volume = {8672}, note = {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.}, abstract = {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.}, ISSN = {1996-756X (Print) 1996-756X (Linking)}, DOI = {10.1117/12.2006492 [doi]}, url = {http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=1674613}, year = {2013}, type = {Journal Article} } @article{ author = {Li, K. and Fei, B.}, title = {A Deformable Model-based Minimal Path Segmentation Method for Kidney MR Images}, journal = {Proc SPIE}, volume = {6914}, note = {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.}, abstract = {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.}, ISSN = {1996-756X (Print) 1996-756X (Linking)}, DOI = {10.1117/12.772347 [doi]}, url = {http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=1329376}, year = {2008}, type = {Journal Article} } @article{ author = {Liu, H. and Wang, J. and Xu, X. and Song, E. and Wang, Q. and Jin, R. and Hung, C. C. and Fei, B.}, title = {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}, journal = {Magn Reson Imaging}, volume = {32}, number = {9}, pages = {1139-55}, note = {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.}, abstract = {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.}, ISSN = {1873-5894 (Electronic) 0730-725X (Linking)}, DOI = {S0730-725X(14)00208-2 [pii] 10.1016/j.mri.2014.07.005 [doi]}, url = {http://ac.els-cdn.com/S0730725X14002082/1-s2.0-S0730725X14002082-main.pdf?_tid=e281ec84-c132-11e4-b38d-00000aab0f6c&acdnat=1425338682_7a3dfa04f9d9e5ad22b77553092e3266}, year = {2014}, type = {Journal Article} } @article{ author = {Lu, G. and Fei, B.}, title = {Medical hyperspectral imaging: a review}, journal = {J Biomed Opt}, volume = {19}, number = {1}, pages = {10901}, note = {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.}, abstract = {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.}, keywords = {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}, ISSN = {1560-2281 (Electronic) 1083-3668 (Linking)}, DOI = {1816617 [pii] 10.1117/1.JBO.19.1.010901 [doi]}, url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3895860/pdf/JBO-019-010901.pdf}, year = {2014}, type = {Journal Article} } @article{ author = {Lu, G. and Halig, L. and Wang, D. and Chen, Z. G. and Fei, B.}, title = {Hyperspectral Imaging for Cancer Surgical Margin Delineation: Registration of Hyperspectral and Histological Images}, journal = {Proc SPIE}, volume = {9036}, pages = {90360S}, note = {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.}, abstract = {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.}, ISSN = {1996-756X (Print) 1996-756X (Linking)}, DOI = {10.1117/12.2043805 [doi]}, url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4201054/pdf/nihms613556.pdf}, year = {2014}, type = {Journal Article} } @article{ author = {Lu, G. and Halig, L. and Wang, D. and Chen, Z. G. and Fei, B.}, title = {Spectral-Spatial Classification Using Tensor Modeling for Cancer Detection with Hyperspectral Imaging}, journal = {Proc SPIE}, volume = {9034}, pages = {903413}, note = {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.}, abstract = {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.}, ISSN = {1996-756X (Print) 1996-756X (Linking)}, DOI = {10.1117/12.2043796 [doi]}, url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4201059/pdf/nihms-613551.pdf}, year = {2014}, type = {Journal Article} } @article{ author = {Lu, G. and Halig, L. and Wang, D. and Qin, X. and Chen, Z. G. and Fei, B.}, title = {Spectral-spatial classification for noninvasive cancer detection using hyperspectral imaging}, journal = {J Biomed Opt}, volume = {19}, number = {10}, pages = {106004}, note = {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.}, abstract = {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.}, ISSN = {1560-2281 (Electronic) 1083-3668 (Linking)}, DOI = {1915159 [pii] 10.1117/1.JBO.19.10.106004 [doi]}, url = {http://biomedicaloptics.spiedigitallibrary.org/article.aspx?articleid=1915159}, year = {2014}, type = {Journal Article} } @article{ author = {Mafi, J. N. and Fei, B. and Roble, S. and Dota, A. and Katrapati, P. and Bezerra, H. G. and Wang, H. and Wang, W. and Ciancibello, L. and Costa, M. and Simon, D. I. and Orringer, C. E. and Gilkeson, R. C.}, title = {Assessment of coronary artery calcium using dual-energy subtraction digital radiography}, journal = {J Digit Imaging}, volume = {25}, number = {1}, pages = {129-36}, note = {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.}, abstract = {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.}, keywords = {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}, ISSN = {1618-727X (Electronic) 0897-1889 (Linking)}, DOI = {10.1007/s10278-011-9385-y [doi]}, url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3264713/pdf/10278_2011_Article_9385.pdf}, year = {2012}, type = {Journal Article} } @article{ author = {Malliori, A. and Bliznakova, K. and Sechopoulos, I. and Kamarianakis, Z. and Fei, B. and Pallikarakis, N.}, title = {Breast tomosynthesis with monochromatic beams: a feasibility study using Monte Carlo simulations}, journal = {Phys Med Biol}, volume = {59}, number = {16}, pages = {4681-96}, note = {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.}, abstract = {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.}, ISSN = {1361-6560 (Electronic) 0031-9155 (Linking)}, DOI = {10.1088/0031-9155/59/16/4681 [doi]}, url = {http://iopscience.iop.org/0031-9155/59/16/4681/}, year = {2014}, type = {Journal Article} } @article{ author = {Pike, R. and Patton, S. K. and Lu, G. and Halig, L. V. and Wang, D. and Chen, Z. G. and Fei, B.}, title = {A Minimum Spanning Forest Based Hyperspectral Image Classification Method for Cancerous Tissue Detection}, journal = {Proc SPIE}, volume = {9034}, pages = {90341W}, note = {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.}, abstract = {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.}, ISSN = {1996-756X (Print) 1996-756X (Linking)}, DOI = {10.1117/12.2043848 [doi]}, url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4241346/pdf/nihms613555.pdf}, year = {2014}, type = {Journal Article} } @article{ author = {Qin, X. and Cong, Z. and Fei, B.}, title = {Automatic segmentation of right ventricular ultrasound images using sparse matrix transform and a level set}, journal = {Phys Med Biol}, volume = {58}, number = {21}, pages = {7609-24}, note = {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.}, abstract = {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.}, keywords = {Algorithms Automation Echocardiography/ methods Endocardium/ultrasonography Heart Ventricles/ ultrasonography Humans Image Processing, Computer-Assisted/ methods Pericardium/ultrasonography}, ISSN = {1361-6560 (Electronic) 0031-9155 (Linking)}, DOI = {10.1088/0031-9155/58/21/7609 [doi]}, url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3925785/pdf/nihms539397.pdf}, year = {2013}, type = {Journal Article} } @article{ author = {Qin, X. and Cong, Z. and Halig, L. V. and Fei, B.}, title = {Automatic Segmentation of Right Ventricle on Ultrasound Images Using Sparse Matrix Transform and Level Set}, journal = {Proc SPIE}, volume = {8669}, note = {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.}, abstract = {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.}, ISSN = {1996-756X (Print) 1996-756X (Linking)}, DOI = {10.1117/12.2006490 [doi]}, url = {http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=1667493}, year = {2013}, type = {Journal Article} } @article{ author = {Qin, X. and Cong, Z. and Jiang, R. and Shen, M. and Wagner, M. B. and Kishbom, P. and Fei, B.}, title = {Extracting Cardiac Myofiber Orientations from High Frequency Ultrasound Images}, journal = {Proc SPIE}, volume = {8675}, note = {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.}, abstract = {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.}, ISSN = {1996-756X (Print) 1996-756X (Linking)}, DOI = {10.1117/12.2006494 [doi]}, url = {http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=1674446}, year = {2013}, type = {Journal Article} } @article{ author = {Qin, X. and Fei, B.}, title = {Measuring myofiber orientations from high-frequency ultrasound images using multiscale decompositions}, journal = {Phys Med Biol}, volume = {59}, number = {14}, pages = {3907-24}, note = {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.}, abstract = {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.}, keywords = {Animals Echocardiography/ methods Heart Ventricles/cytology Humans Image Processing, Computer-Assisted/ methods Myocardium/ cytology Phantoms, Imaging Swine}, ISSN = {1361-6560 (Electronic) 0031-9155 (Linking)}, DOI = {10.1088/0031-9155/59/14/3907 [doi]}, url = {http://iopscience.iop.org/0031-9155/59/14/3907/}, year = {2014}, type = {Journal Article} } @article{ author = {Qin, X. and Lu, G. and Sechopoulos, I. and Fei, B.}, title = {Breast Tissue Classification in Digital Tomosynthesis Images Based on Global Gradient Minimization and Texture Features}, journal = {Proc SPIE}, volume = {9034}, pages = {90341V}, note = {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.}, abstract = {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.}, ISSN = {1996-756X (Print) 1996-756X (Linking)}, DOI = {10.1117/12.2043828 [doi]}, url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4241347/pdf/nihms613554.pdf}, year = {2014}, type = {Journal Article} } @article{ author = {Qin, X. and Wang, S. and Shen, M. and Zhang, X. and Wagner, M. B. and Fei, B.}, title = {Mapping Cardiac Fiber Orientations from High-Resolution DTI to High-Frequency 3D Ultrasound}, journal = {Proc SPIE}, volume = {9036}, pages = {90361O}, note = {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.}, abstract = {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.}, ISSN = {1996-756X (Print) 1996-756X (Linking)}, DOI = {10.1117/12.2043821 [doi]}, url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4201058/pdf/nihms613557.pdf}, year = {2014}, type = {Journal Article} } @article{ author = {Schuster, D. M. and Taleghani, P. A. and Nieh, P. T. and Master, V. A. and Amzat, R. and Savir-Baruch, B. and Halkar, R. K. and Fox, T. and Osunkoya, A. O. and Moreno, C. S. and Nye, J. A. and Yu, W. and Fei, B. and Wang, Z. and Chen, Z. and Goodman, M. M.}, title = {Characterization of primary prostate carcinoma by anti-1-amino-2-[(18)F] -fluorocyclobutane-1-carboxylic acid (anti-3-[(18)F] FACBC) uptake}, journal = {Am J Nucl Med Mol Imaging}, volume = {3}, number = {1}, pages = {85-96}, note = {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.}, abstract = {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.}, ISSN = {2160-8407 (Electronic)}, url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3545368/pdf/ajnmmi0003-0085.pdf}, year = {2013}, type = {Journal Article} } @article{ author = {Sechopoulos, I. and Bliznakova, K. and Fei, B.}, title = {Power spectrum analysis of the x-ray scatter signal in mammography and breast tomosynthesis projections}, journal = {Med Phys}, volume = {40}, number = {10}, pages = {101905}, note = {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.}, abstract = {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.}, keywords = {Breast Humans Image Processing, Computer-Assisted/ methods Mammography/ methods Monte Carlo Method X-Ray Diffraction}, ISSN = {0094-2405 (Print) 0094-2405 (Linking)}, DOI = {10.1118/1.4820442 [doi]}, url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3785536/pdf/MPHYA6-000040-101905_1.pdf}, year = {2013}, type = {Journal Article} } @article{ author = {Sechopoulos, I. and Bliznakova, K. and Qin, X. and Fei, B. and Feng, S. S.}, title = {Characterization of the homogeneous tissue mixture approximation in breast imaging dosimetry}, journal = {Med Phys}, volume = {39}, number = {8}, pages = {5050-9}, note = {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.}, abstract = {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.}, keywords = {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}, ISSN = {0094-2405 (Print) 0094-2405 (Linking)}, DOI = {10.1118/1.4737025 [doi]}, url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3416880/pdf/MPHYA6-000039-005050_1.pdf}, year = {2012}, type = {Journal Article} } @article{ author = {Wang, H. and Fei, B.}, title = {A modified fuzzy C-means classification method using a multiscale diffusion filtering scheme}, journal = {Med Image Anal}, volume = {13}, number = {2}, pages = {193-202}, note = {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.}, abstract = {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.}, keywords = {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}, ISSN = {1361-8423 (Electronic) 1361-8415 (Linking)}, DOI = {S1361-8415(08)00071-6 [pii] 10.1016/j.media.2008.06.014 [doi]}, url = {http://ac.els-cdn.com/S1361841508000716/1-s2.0-S1361841508000716-main.pdf?_tid=2afc2ccc-c133-11e4-a721-00000aab0f27&acdnat=1425338803_1261da35e2cadec8f458c202f50d408a}, year = {2009}, type = {Journal Article} } @article{ author = {Wang, H. and Fei, B.}, title = {An MRI-guided PET Partial Volume Correction Method}, journal = {Proc SPIE}, volume = {7259}, note = {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.}, abstract = {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.}, ISSN = {1996-756X (Print) 1996-756X (Linking)}, DOI = {10.1117/12.812474 [doi]}, url = {http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=1335548}, year = {2009}, type = {Journal Article} } @article{ author = {Wang, H. and Fei, B.}, title = {Diffusion-weighted MRI for monitoring tumor response to photodynamic therapy}, journal = {J Magn Reson Imaging}, volume = {32}, number = {2}, pages = {409-17}, note = {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.}, abstract = {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.}, keywords = {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}, ISSN = {1522-2586 (Electronic) 1053-1807 (Linking)}, DOI = {10.1002/jmri.22247 [doi]}, url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3076282/pdf/nihms255624.pdf}, year = {2010}, type = {Journal Article} } @article{ author = {Wang, H. and Fei, B.}, title = {An MR image-guided, voxel-based partial volume correction method for PET images}, journal = {Med Phys}, volume = {39}, number = {1}, pages = {179-95}, note = {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.}, abstract = {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.}, keywords = {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}, ISSN = {0094-2405 (Print) 0094-2405 (Linking)}, DOI = {10.1118/1.3665704 [doi]}, url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3261055/pdf/MPHYA6-000039-000179_1.pdf}, year = {2012}, type = {Journal Article} } @article{ author = {Wang, H. and Fei, B.}, title = {Nonrigid point registration for 2D curves and 3D surfaces and its various applications}, journal = {Phys Med Biol}, volume = {58}, number = {12}, pages = {4315-30}, note = {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.}, abstract = {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.}, keywords = {Animals Imaging, Three-Dimensional/ methods Magnetic Resonance Imaging Mice Photochemotherapy Surface Properties Whole Body Imaging X-Ray Microtomography}, ISSN = {1361-6560 (Electronic) 0031-9155 (Linking)}, DOI = {10.1088/0031-9155/58/12/4315 [doi]}, url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3819195/pdf/nihms491238.pdf}, year = {2013}, type = {Journal Article} } @article{ author = {Wang, H. and Feyes, D. and Mulvihill, J. and Oleinick, N. and Maclennan, G. and Fei, B.}, title = {Multiscale Fuzzy C-Means Image Classification for Multiple Weighted MR Images for the Assessment of Photodynamic Therapy in Mice}, journal = {Proc SPIE}, volume = {6512}, note = {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.}, abstract = {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.}, ISSN = {1996-756X (Print) 1996-756X (Linking)}, DOI = {10.1117/12.710188 [doi]}, url = {http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=1336682}, year = {2007}, type = {Journal Article} } @article{ author = {Wooten, W. J., 3rd and Nye, J. A. and Schuster, D. M. and Nieh, P. T. and Master, V. A. and Votaw, J. R. and Fei, B.}, title = {Accuracy Evaluation of a 3D Ultrasound-guided Biopsy System}, journal = {Proc SPIE}, volume = {8671}, note = {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.}, abstract = {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.}, ISSN = {1996-756X (Print) 1996-756X (Linking)}, DOI = {10.1117/12.2007695 [doi]}, url = {http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=1668869}, year = {2013}, type = {Journal Article} } @article{ author = {Yang, X. and Akbari, H. and Halig, L. and Fei, B.}, title = {3D Non-rigid Registration Using Surface and Local Salient Features for Transrectal Ultrasound Image-guided Prostate Biopsy}, journal = {Proc SPIE}, volume = {7964}, pages = {79642V}, note = {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.}, abstract = {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.}, ISSN = {1996-756X (Print) 1996-756X (Linking)}, DOI = {10.1117/12.878153 [doi]}, url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3766999/pdf/nihms362780.pdf}, year = {2011}, type = {Journal Article} } @article{ author = {Yang, X. and Fei, B.}, title = {A MR Brain Classification Method Based on Multiscale and Multiblock Fuzzy C-means}, journal = {Int Conf Bioinform Biomed Eng}, pages = {1-4}, note = {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.}, abstract = {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.}, ISSN = {2151-7614 (Print) 2151-7614 (Linking)}, year = {2011}, type = {Journal Article} } @article{ author = {Yang, X. and Fei, B.}, title = {A multiscale and multiblock fuzzy C-means classification method for brain MR images}, journal = {Med Phys}, volume = {38}, number = {6}, pages = {2879-91}, note = {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.}, abstract = {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.}, keywords = {Algorithms Brain Humans Image Processing, Computer-Assisted/ methods Magnetic Resonance Imaging/ methods}, ISSN = {0094-2405 (Print) 0094-2405 (Linking)}, url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3117893/pdf/MPHYA6-000038-002879_1.pdf}, year = {2011}, type = {Journal Article} } @article{ author = {Yang, X. and Fei, B.}, title = {A wavelet multiscale denoising algorithm for magnetic resonance (MR) images}, journal = {Meas Sci Technol}, volume = {22}, number = {2}, pages = {25803}, note = {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.}, abstract = {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.}, ISSN = {0957-0233 (Print) 0957-0233 (Linking)}, DOI = {10.1088/0957-0233/22/2/025803 [doi]}, url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3707516/pdf/nihms362727.pdf}, year = {2011}, type = {Journal Article} } @article{ author = {Yang, X. and Fei, B.}, title = {3D Prostate Segmentation of Ultrasound Images Combining Longitudinal Image Registration and Machine Learning}, journal = {Proc SPIE}, volume = {8316}, pages = {83162O}, note = {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.}, abstract = {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.}, ISSN = {1996-756X (Print) 1996-756X (Linking)}, DOI = {10.1117/12.912188 [doi]}, url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3767004/pdf/nihms362793.pdf}, year = {2012}, type = {Journal Article} } @article{ author = {Yang, X. and Fei, B.}, title = {Multiscale segmentation of the skull in MR images for MRI-based attenuation correction of combined MR/PET}, journal = {J Am Med Inform Assoc}, volume = {20}, number = {6}, pages = {1037-45}, note = {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.}, abstract = {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.}, keywords = {Brain/ pathology/radionuclide imaging Diagnosis, Computer-Assisted Humans Magnetic Resonance Imaging/ methods Mathematical Concepts Phantoms, Imaging Positron-Emission Tomography/ methods Skull/ pathology/radionuclide imaging}, ISSN = {1527-974X (Electronic) 1067-5027 (Linking)}, DOI = {amiajnl-2012-001544 [pii] 10.1136/amiajnl-2012-001544 [doi]}, url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3822115/pdf/amiajnl-2012-001544.pdf}, year = {2013}, type = {Journal Article} } @article{ author = {Yang, X. and Ghafourian, P. and Sharma, P. and Salman, K. and Martin, D. and Fei, B.}, title = {Nonrigid Registration and Classification of the Kidneys in 3D Dynamic Contrast Enhanced (DCE) MR Images}, journal = {Proc SPIE}, volume = {8314}, pages = {83140B}, note = {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.}, abstract = {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.}, ISSN = {1996-756X (Print) 1996-756X (Linking)}, DOI = {10.1117/12.912190 [doi]}, url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3314431/pdf/nihms362796.pdf}, year = {2012}, type = {Journal Article} } @article{ author = {Yang, X. and Schuster, D. and Master, V. and Nieh, P. and Fenster, A. and Fei, B.}, title = {Automatic 3D Segmentation of Ultrasound Images Using Atlas Registration and Statistical Texture Prior}, journal = {Proc SPIE}, volume = {7964}, note = {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.}, abstract = {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.}, ISSN = {1996-756X (Print) 1996-756X (Linking)}, DOI = {10.1117/12.877888 [doi]}, url = {http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=1349950}, year = {2011}, type = {Journal Article} } @article{ author = {Yang, X. and Sechopoulos, I. and Fei, B.}, title = {Automatic Tissue Classification for High-resolution Breast CT Images Based on Bilateral Filtering}, journal = {Proc SPIE}, volume = {7962}, pages = {79623H}, note = {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.}, abstract = {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.}, ISSN = {1996-756X (Print) 1996-756X (Linking)}, DOI = {10.1117/12.877881 [doi]}, url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3766982/pdf/nihms362783.pdf}, year = {2011}, type = {Journal Article} } @article{ author = {Yang, X. and Wu, S. and Sechopoulos, I. and Fei, B.}, title = {Cupping artifact correction and automated classification for high-resolution dedicated breast CT images}, journal = {Med Phys}, volume = {39}, number = {10}, pages = {6397-406}, note = {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.}, abstract = {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.}, keywords = {Artifacts Automation Breast/ cytology/pathology Humans Image Processing, Computer-Assisted/ methods Mammography/ methods Phantoms, Imaging Tomography, X-Ray Computed/ methods}, ISSN = {0094-2405 (Print) 0094-2405 (Linking)}, DOI = {10.1118/1.4754654 [doi]}, url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3477198/pdf/MPHYA6-000039-006397_1.pdf}, year = {2012}, type = {Journal Article} }