@article{ author = {Akbari, H. and Fei, B. W.}, title = {3D ultrasound image segmentation using wavelet support vector machines}, journal = {Medical Physics}, volume = {39}, number = {6}, pages = {2972-2984}, note = {Akbari, Hamed Fei, Baowei}, 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. (C) 2012 American Association of Physicists in Medicine. [http://dx.doi.org/10.1118/1.4709607]}, year = {2012} } @inbook{ author = {Akbari, H. and Fei, B. W.}, title = {Automatic 3D Segmentation of the Kidney in MR Images Using Wavelet Feature Extraction and Probability Shape Model}, booktitle = {Medical Imaging 2012: Image Processing}, editor = {Haynor, D. R. and Ourselin, S.}, series = {Proceedings of SPIE}, volume = {8314}, note = {Akbari, Hamed Fei, Baowei Conference on Medical Imaging - Image Processing Feb 06-09, 2012 San Diego, CA SPIE, Agilent Technol, Diamond SA, DQE Instruments Inc, eMagin, Isuzu Glass Co Ltd, Medtron Inc, Ocean Thin Films Inc}, 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.}, year = {2012} } @inbook{ author = {Akbari, H. and Fei, B. W.}, title = {Automatic 3D Segmentation of the Kidney in MR Images Using Wavelet Feature Extraction and Probability Shape Model}, booktitle = {Medical Imaging 2012: Image Processing}, editor = {Haynor, D. R. and Ourselin, S.}, series = {Proceedings of SPIE}, volume = {8314}, note = {Akbari, Hamed Fei, Baowei Conference on Medical Imaging - Image Processing Feb 06-09, 2012 San Diego, CA SPIE, Agilent Technol, Diamond SA, DQE Instruments Inc, eMagin, Isuzu Glass Co Ltd, Medtron Inc, Ocean Thin Films Inc}, 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.}, year = {2012} } @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. W.}, title = {Hyperspectral imaging and quantitative analysis for prostate cancer detection}, journal = {J Biomed Opt}, volume = {17}, number = {7}, note = {Akbari, Hamed Halig, Luma V. Schuster, David M. Osunkoya, Adeboye Master, Viraj Nieh, Peter T. Chen, Georgia Z. Fei, Baowei}, 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. (C) 2012 Society of Photo-Optical Instrumentation Engineers (SPIE). [DOI: 10.1117/1.JBO.17.7.076005]}, year = {2012} } @inbook{ author = {Akbari, H. and Halig, L. V. and Zhang, H. Z. and Wang, D. S. and Chen, Z. G. and Fei, B. W.}, title = {Detection of Cancer Metastasis Using a Novel Macroscopic Hyperspectral Method}, booktitle = {Medical Imaging 2012: Biomedical Applications in Molecular, Structural, and Functional Imaging}, editor = {Molthen, R. C. and Weaver, J. B.}, series = {Proceedings of SPIE}, volume = {8317}, note = {Akbari, Hamed Halig, Luma V. Zhang, Hongzheng Wang, Dongsheng Chen, Zhuo Georgia Fei, Baowei Conference on Medical Imaging - Biomedical Applications in Molecular, Structural and Functional Imaging Feb 05-07, 2012 San Diego, CA SPIE, Agilent Technol, Diamond SA, DQE Instruments Inc, eMagin, Isuzu Glass Co Ltd, Medtron Inc, Ocean Thin Films Inc}, 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.}, year = {2012} } @inbook{ author = {Akbari, H. and Yang, X. F. and Halig, L. V. and Fei, B. W.}, title = {3D Segmentation of Prostate Ultrasound images Using Wavelet Transform}, booktitle = {Medical Imaging 2011: Image Processing}, editor = {Dawant, B. M. and Haynor, D. R.}, series = {Proceedings of SPIE}, volume = {7962}, note = {Akbari, Hamed Yang, Xiaofeng Halig, Luma V. Fei, Baowei Conference on Medical Imaging 2011 - Image Processing Feb 14-16, 2011 Lake Buena Vista, FL Dynasil Corp/RMD Res, Amer Assoc Physicists Med, DQE Instruments Inc, Ocean Thin Films, Inc, Univ Cent Florida, CREOL - Coll Opt & Photon, VIDA Diagnost, Inc, SPIE}, 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.}, year = {2011} } @inbook{ author = {Bebek, O. and Hwang, M. J. and Fei, B. W. and Cavusoglu, M. C. and Ieee}, title = {Design of a Small Animal Biopsy Robot}, booktitle = {2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Vols 1-8}, series = {IEEE Engineering in Medicine and Biology Society Conference Proceedings}, pages = {5601-5604}, note = {Bebek, Ozkan Hwang, Myun Joong Fei, Baowei Cavusoglu, M. Cenk 30th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society Aug 20-24, 2008 Vancouver, CANADA DEVICIX, Green Coll, Natl Inst Hlth, NIBIB, NSF, PLEXON Inc, UBC Engn Biomed Engn, Univ Washington, Coll Engn, Bentham Sci Publ Ltd, Recent Patents Biomed Engn, Recent Patents Engn}, 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.}, year = {2008} } @article{ author = {Bogie, K. and Wang, X. F. and Fei, B. W. and Sun, J. Y.}, title = {New technique for real-time interface pressure analysis: Getting more out of large image data sets}, journal = {Journal of Rehabilitation Research and Development}, volume = {45}, number = {4}, pages = {523-535}, note = {Bogie, Kath Wang, Xiaofeng Fei, Baowei Sun, Jiayang}, 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 modem 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.}, year = {2008} } @article{ author = {Chen, X. and Gilkeson, R. C. and Fei, B. W.}, title = {Automatic 3D-to-2D registration for CT and dual-energy digital radiography for calcification detection}, journal = {Medical Physics}, volume = {34}, number = {12}, pages = {4934-4943}, note = {Chen, Xiang Gilkeson, Robert C. Fei, Baowei}, 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.}, year = {2007} } @inbook{ author = {Chen, X. and Gilkeson, R. and Fei, B. W.}, title = {Automatic intensity-based 3D-to-2D registration of CT volume and dual-energy digital radiography for the detection of cardiac calcification - art. no. 65120A}, booktitle = {Medical Imaging 2007: Image Processing, Pts 1-3}, editor = {Pluim, J. P. W. and Reinhardt, J. M.}, series = {Proceedings of the Society of Photo-Optical Instrumentation Engineers (Spie)}, volume = {6512}, pages = {A5120-A5120}, note = {Chen, Xiang Gilkeson, Robert Fei, Baowei Medical Imaging 2007 Conference Feb 18-20, 2007 San Diego, CA SPIE, Amer Assoc Physicists, Amer Physiol Soc, Comp Assisted Radiol & Surg, Soc Imaging Sci & Technol, Med Image Percept Soc, Radiol Soc N Amer, Soc Imaging Informat Med, Soc Mole Imaging, DICOM Standards Comm}, abstract = {We are investigating three-dimensional (3D) to two-dimensional (213) 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.}, year = {2007} } @inbook{ author = {Chen, X. and Li, K. and Gilkeson, R. and Fei, B. W.}, title = {Gaussian weighted projection for visualization of cardiac calcification - art. no. 691831}, booktitle = {Medical Imaging 2008: Visualization, Image-Guided Procedures, and Modeling, Pts 1 and 2}, editor = {Miga, M. I. and Cleary, K. R.}, series = {Proceedings of the Society of Photo-Optical Instrumentation Engineers (Spie)}, volume = {6918}, pages = {91831-91831}, note = {Chen, Xiang Li, Ke Gilkeson, Robert Fei, Bawei Medical Imaging 2008 Conference Feb 17-19, 2008 San Diego, CA SPIE, Amer Assoc Phys Med, Amer Physiol Soc, Comp Assisted Radiol & Surg, Soc Imaging Sci & Technol, Med Image Percept Soc, Radiol Soc N Amer, Soc Imaging Informat Med, Soc Mole Imaging, DICOM Standards Comm}, 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 MLP method and can be used to evaluate DEDR as a screening tool for the detection of coronary artery diseases.}, year = {2008} } @article{ author = {Cheng, Y. and Samia, A. C. and Meyers, J. D. and Panagopoulos, I. and Fei, B. W. and Burda, C.}, title = {Highly efficient drug delivery with gold nanoparticle vectors for in vivo photodynamic therapy of cancer}, journal = {Journal of the American Chemical Society}, volume = {130}, number = {32}, pages = {10643-10647}, note = {Cheng, Yu Samia, Anna C. Meyers, Joseph D. Panagopoulos, Irene Fei, Baowei Burda, Clemens}, 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.}, year = {2008} } @article{ author = {Ciancibello, L. and Gilkeson, R. and Fei, B.}, title = {Bismuth Breast Shielding and its Effect on Calcium Score and Dose}, journal = {American Journal of Roentgenology}, volume = {192}, number = {5}, note = {Ciancibello, L. Gilkeson, R. Fei, B. 109th Annual Meeting of the American-Roentgen-Ray-Society Apr 27-may 01, 2009 Boston, MA Amer Roentgen Ray Soc}, year = {2009} } @article{ author = {Fei, B. and Schuster, D. and Master, V. and Nieh, P.}, title = {Incorporating PET/CT Images Into 3D Ultrasound-Guided Biopsy of the Prostate}, journal = {Medical Physics}, volume = {39}, number = {6}, pages = {3888-3888}, note = {Fei, B. Schuster, D. Master, V. Nieh, P. 54th Annual Meeting and Exhibition of the American-Association-of-Physicists-in-Medicine (AAPM) Jul 29-aug 02, 2012 Charlotte, NC Amer Assoc Physicists Med (AAPM)}, year = {2012} } @inbook{ author = {Fei, B. W. and Boll, D. T. and Duerk, J. L. and Wilson, D. L. and Ieee}, title = {Image registration for interventional MRI-guided minimally invasive treatment of prostate cancer}, booktitle = {Second Joint Embs-Bmes Conference 2002, Vols 1-3, Conference Proceedings: Bioengineering - Integrative Methodologies, New Technologies}, series = {Proceedings of Annual International Conference of the Ieee Engineering in Medicine and Biology Society}, pages = {1185-1185}, note = {Fei, BW Boll, DT Duerk, JL Wilson, DL 24th Annual International Conference of the Engineering-in-Medicine-and-Biology-Society/Annual Fall Meeting of the Biomedical-Engineering-Society (EMBS 2002 BMES) Oct 23-26, 2002 Houston, tx Engn Med & Biol Soc, Biomed Engn Soc, Natl Sci Fdn, Natl Inst Hlth, Natl Inst Biomed Imaging & Bioengn, Whitaker Fdn}, abstract = {We are investigating automatic image registration methods that can be used for interventional magnetic resonance imaging (iMRI) guided radiofrequency (RF) thermal ablation of prostate cancer. We tested the ability of slice-to-volume registration between iMRI slice images and high-resolution MRI volumes. Images were acquired from a conventional 1.5 T and an interventional 0.2 T MRI system. We evaluated the registration quality by calculating 3D displacement on a voxel-by-voxel basis over a volume of interest between slice-to-volume registration and volume-to-volume registration that was previously shown to be quite accurate. Visual inspections such as color overlay and contour overlap were also used for registration evaluation. More than 300 registration experiments were performed on MR images of volunteers. Results showed that the registration was quite robust and accurate (< 2 mm) for the transverse images covering the prostate.}, year = {2002} } @book{ author = {Fei, B. W. and Chen, X. and Wang, H. S. and Sabol, J. M. and DuPont, E. and Gilkeson, R. C. and Ieee}, title = {Automatic registration of CT volumes and dual-energy digital radiography for detection of cardiac and lung diseases}, series = {2006 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Vols 1-15}, note = {Fei, Baowei Chen, Xiang Wang, Hesheng Sabol, John M. DuPont, Elena Gilkeson, Robert C. 28th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society Aug 30-sep 03, 2006 New York, NY IEEE Engn Med & Biol Sci}, 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 dualenergy 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 regis tration is accurate and useful for this new application.}, pages = {40-43}, year = {2006} } @article{ author = {Fei, B. W. 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 Transactions on Medical Imaging}, volume = {22}, number = {4}, pages = {515-525}, note = {Fei, BW Duerk, JL Boll, DT Lewin, JS Wilson, DL}, 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.}, year = {2003} } @article{ author = {Fei, B. W. and Duerk, J. L. and Sodee, D. B. and Wilson, D. L.}, title = {Semiautomatic nonrigid registration for the prostate and pelvic MR volumes}, journal = {Academic Radiology}, volume = {12}, number = {7}, pages = {815-824}, note = {Fei, BW Duerk, JL Sodee, DB Wilson, DL}, 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.}, year = {2005} } @inbook{ author = {Fei, B. W. and Flask, C. and Wang, H. S. and Pi, A. and Wilson, D. L. and Shillingford, J. and Murcia, N. and Weimbs, T. and Duerk, J. L. and Ieee}, title = {Image segmentation, registration and visualization of serial MR images for therapeutic assessment of polycystic kidney disease in transgenic mice}, booktitle = {2005 27th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Vols 1-7}, series = {Proceedings of Annual International Conference of the Ieee Engineering in Medicine and Biology Society}, pages = {467-469}, note = {Fei, Baowei Flask, Chris Wang, Hesheng Pi, Al Wilson, David L. Shillingford, Jonathan Murcia, Noel Weimbs, Thomas Duerk, Jeffrey L. 27th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society Aug 31-sep 03, 2005 Shanghai, PEOPLES R CHINA IEEE Engn Med & Biol Soc, Chinese Acad Engn Sci}, 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 mm(3) for wild-type mice and 756.3 +/- 44.1 mm(3) for transgenic mice, respectively. The image analysis methods provide a useful tool for this new application.}, year = {2005} } @inbook{ author = {Fei, B. W. and Frinkley, K. and Wilson, D. L.}, title = {Registration algorithms for interventional. MRI-guided treatment of the prostate}, booktitle = {Medical Imaging 2003: Visualization, Image-Guided Procedures, and Display}, editor = {Galloway, R. L.}, series = {Proceedings of the Society of Photo-Optical Instrumentation Engineers (Spie)}, volume = {5029}, pages = {192-201}, note = {Fei, BW Frinkley, K Wilson, DL Medical Imaging 2003 Conference Feb 17-20, 2003 San diego, ca SPIE, Amer Assoc Phys Med, Amer Physiol Soc, Ctr Devices & Radiol Hlth, Soc Imaging Sci & Technol, Natl Elect Mfg Assoc, Diagnost Imaging & Therapy Syst Div, Radiol Soc N Amer, Soc Comp Appl Radiol}, abstract = {We are investigating interventional MRI (iMRI) guided radiofrequency thermal ablation for the minimally invasive treatment of prostate cancer. Nuclear medicine and MR spectroscopy can detect and localize tumor in the prostate not reliably seen in MR. We are investigating methods to combine the advantages of functional images such as SPECT with iMRI-guided treatments. Our concept is to first register the low-resolution functional images with a high resolution MR volume. Then by registering the high-resolution MR image with live-time iMRI acquisitions, we can, in turn, map the functional data and high-resolution anatomic information to iMRI images for improved tumor targeting. In this study, we registered noisy, thick iMRI image slices with high-resolution MR volumes and called this slice-to-volume registration. We investigated two similarity measures, i.e., mutual information and correlation coefficient, and three interpolation methods, i.e., tri-linear, re-normalized sinc, and nearest neighbor. To assess the quality of registration, we calculated 3D displacement on a voxel-by-voxel basis over a volume of interest (VOI) between slice-to-volume registration and volume-to-volume registration that was previously shown to be quite accurate for these image pairs. Over 300 registration experiments showed that transverse slice images covering the prostate work best with a registration error of only 0.4 +/- 0.2 mm. Error was greater at other slice orientations and positions. Since live-time iMRI images are used for guidance and registered images are used for adjunctive information, the accuracy and robustness of slice-to-volume registration is very probably adequate.}, year = {2003} } @inbook{ author = {Fei, B. W. and Kemper, C. and Wilson, D. L.}, title = {Three-dimensional warping registration of the pelvis and prostate}, booktitle = {Medical Imaging 2002: Image Processing, Vol 1-3}, editor = {Sonka, M. and Fitzpatrick, J. M.}, series = {Proceedings of the Society of Photo-Optical Instrumentation Engineers (Spie)}, volume = {4684}, pages = {528-537}, note = {Fei, BW Kemper, C Wilson, DL Medical Imaging 2002 Conference Feb 24-28, 2002 San diego, ca SPIE, Amer Assoc Phys Med, Amer Physiol Soc, FDA Ctr Devices & Radiol Hlth, Soc Imaging Sci & Technol, Natl Elect Mfg Assoc, Diagnost Imaging & Therapy Syst Div, Radiol Soc N Amer, Soc Comp Applicat Radiol}, abstract = {We are investigating interventional MRI guided radiofrequency (RF) thermal ablation for the minimally invasive treatment of prostate cancer. Among many potential applications of registration, we wish to compare registered MR images acquired before and immediately after RF ablation in order to determine whether a tumor is adequately treated. Warping registration is desired to correct for potential deformations of the pelvic region and movement of the prostate. We created a two-step, three-dimensional (3D) registration algorithm using mutual information and thin plate spline (TPS) warping for MR images. First, automatic rigid body registration was used to capture the global transformation. Second, local warping registration was applied. Interactively placed control points were automatically optimized by maximizing the mutual information of corresponding voxels in small volumes of interest and by using a 3D TPS to express the deformation throughout the image volume. Images were acquired from healthy volunteers in different conditions simulating potential applications. A variety of evaluation methods showed that warping consistently improved registration for volume pairs whenever patient position or condition was purposely changed between acquisitions. A TPS transformation based on 180 control points generated excellent warping throughout the pelvis following rigid body registration. The prostate centroid displacement for a typical volume pair was reduced from 3.4 mm to 0.6 mm when warping was added.}, year = {2002} } @article{ author = {Fei, B. W. 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 = {Computerized Medical Imaging and Graphics}, volume = {27}, number = {4}, pages = {267-281}, note = {Fei, BW Kemper, C Wilson, DL}, 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 approximate to 180 strategically placed CP's were sufficiently expressive to capture important features of the deformation. (C) 2002 Elsevier Science Ltd. All rights reserved.}, year = {2003} } @inbook{ author = {Fei, B. W. and Lee, Z. H. and Boll, D. T. and Duerk, J. L. and Lewin, J. S. and Wilson, D. L.}, title = {Image registration and fusion for interventional MRI guided thermal ablation of the prostate cancer}, booktitle = {Medical Image Computing and Computer-Assisted Intervention - Miccai 2003, Pt 2}, editor = {Ellis, R. E. and Peters, T. M.}, series = {Lecture Notes in Computer Science}, volume = {2879}, pages = {364-372}, note = {Fei, BW Lee, ZH Boll, DT Duerk, JL Lewin, JS Wilson, DL 6th International Conference on Medical Image Computing and Computer-Assisted Intervention Nov 15-18, 2003 Montreal, canada Robarts Res Inst, No Digital Inc}, abstract = {We are investigating interventional MRI (iMRI) guided thermal ablation treatment of the prostate cancer. Functional images such as SPECT can detect and localize tumor in the prostate not reliably seen in MRI. We intend to combine the advantages of SPECT with iMRI-guided treatments. Our concept is to first register the low-resolution SPECT with a high resolution MRI volume. Then by registering the high-resolution MR image with iMRI acquisitions, we can, in turn, map the functional data and high-resolution anatomic information to iMRI images for improved tumor targeting. For the first step, we used a mutual information registration method. For the latter, we developed a robust slice to volume (SV) registration algorithm. Image data were acquired from patients and volunteers. Compared to our volume-to-volume registration that was previously evaluated to be quite accurate, the SV registration accuracy is about 0.5 nun for transverse images covering the prostate. With our image registration and fusion software, simulation experiments show that it is feasible to incorporate SPECT and high resolution MRI into the iMRI-guided treatment.}, year = {2003} } @article{ author = {Fei, B. W. and Lee, Z. H. and Boll, D. T. and Duerk, J. L. and Sodee, D. B. and Lewin, J. S. and Wilson, D. L.}, title = {Registration and fusion of SPECT, high-resolution MRI, and interventional MRI for thermal ablation of prostate cancer}, journal = {Ieee Transactions on Nuclear Science}, volume = {51}, number = {1}, pages = {177-183}, note = {Fei, BW Lee, ZH Boll, DT Duerk, JL Sodee, DB Lewin, JS Wilson, DL Part 1}, abstract = {We are investigating interventional MRI (iMRI) guided radiofrequency thermal ablation for the minimally invasive treatment of the prostate cancer. Nuclear medicine can detect and localize tumor in the prostate not reliably seen in MRI. We intend to combine the advantages of functional images such as nuclear medicine SPECT with iMRI-guided treatments. Our concept is to first register the low-resolution SPECT with a high-resolution MRI volume. Then by registering the high-resolution MR image with live-time iMRI acquisitions, we can, in turn, map the functional data and high-resolution anatomic information to live-time iMRI images for improved tumor targeting. For the first step, we used a three-dimensional mutual information registration method. For the latter, we developed a robust slice to volume (SV) registration algorithm with special features. The concept was tested using image data from three patients and three volunteers. The SV registration accuracy was 0.4 mm +/- 0.2 mm as compared to our volume-to-volume registration that was previously shown to be quite accurate for these image pairs. With our image registration and fusion software, simulation experiments show that it is quite feasible to incorporate SPECT and high-resolution MRI into the iMRI-guided minimally invasive treatment procedures.}, year = {2004} } @inbook{ author = {Fei, B. W. and Lee, Z. H. and Duerk, J. L. and Wilson, D. L.}, title = {Image registration for interventional MRI guided procedures: Interpolation methods, similarity measurements, and applications to the prostate}, booktitle = {Biomedical Image Registration}, editor = {Gee, J. C. and Maintz, J. B. A. and Vannier, M. W.}, series = {Lecture Notes in Computer Science}, volume = {2717}, pages = {321-329}, note = {Fei, BW Lee, ZH Duerk, JL Wilson, DL 2nd International Workshop on Biomedical Image Registration Jun 23-24, 2003 Philadelphia, pa Siemens Med Solut, Siemens Corp Res, Natl Lib Med, Univ Penn, Vice Provost Res}, abstract = {Nuclear medicine can detect and localize tumor in the prostate not reliably seen in MR. We are investigating methods to combine the advantages of SPECT with interventional MRI (iMRI) guided radiofrequency thermal ablation of the prostate. Our approach is to first register the low-resolution functional images with a high resolution MR volume. Then, by combining the high-resolution MR image with live-time iMRI acquisitions, we can, in turn, include the functional data and high-resolution anatomic information into the iMRI system for improved tumor targeting. In this study, we investigated registration methods for combining noisy, thick iMRI image slices with high-resolution MR volumes. We compared three similarity measures, i.e., normalized mutual information, mutual information, and correlation coefficient; and three interpolation methods, i.e., re-normalized sine, tri-linear, and nearest neighbor. Registration experiments showed that transverse slice images covering the prostate work best with a registration error of approximate to 0.5 mm as compared to our volume-to-volume registration that was previously shown to be quite accurate for these image pairs.}, year = {2003} } @inbook{ author = {Fei, B. W. and Master, V. and Nieh, P. and Akbari, H. and Yang, X. F. and Fenster, A. and Schuster, D.}, title = {A PET/CT Directed, 3D Ultrasound-Guided Biopsy System for Prostate Cancer}, booktitle = {Prostate Cancer Imaging: Image Analysis and Image-Guided Interventions}, editor = {Madabhushi, A. and Dowling, J. and Huisman, H. and Barratt, D.}, series = {Lecture Notes in Computer Science}, volume = {6963}, pages = {100-108}, note = {Fei, Baowei Master, Viraj Nieh, Peter Akbari, Hamed Yang, Xiaofeng Fenster, Aaron Schuster, David 14th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2011) Sep 18-22, 2011 Toronto, CANADA}, abstract = {Prostate cancer affects I in 6 men in the USA. Systematic transrectal ultrasound (TRUS)-guided biopsy is the standard method for a definitive diagnosis of prostate cancer. However, this "blind" biopsy approach can miss at least 20% of prostate cancers. In this study, we are developing a PET/CT directed, 3D ultrasound image-guided biopsy system for improved detection of prostate cancer. In order to plan biopsy in three dimensions, we developed an automatic segmentation method based wavelet transform for 3D TRUS images of the prostate. The segmentation was tested in five patients with a DICE overlap ratio of more than 91%. In order to incorporate PET/CT images into ultrasound-guided biopsy, we developed a nonrigid registration algorithm for TRUS and PET/CT images. The registration method has been tested in a prostate phantom with a target registration error (TRE) of less than 0.4 mm. The segmentation and registration methods are two key components of the multimodality molecular image-guided biopsy system.}, year = {2011} } @inbook{ author = {Fei, B. W. and Muzic, R. F. and Lee, Z. and Flask, C. A. and Morris, R. L. and Duerk, J. L. and Oleinick, N. and Wilson, D. L.}, title = {Registration of micro-PET and high resolution MR images of mice for monitoring photodynamic therapy}, booktitle = {Medical Imaging 2004: Physiology, Function, and Structure from Medical Images}, editor = {Amini, A. A. and Manduca, A.}, series = {Progress in Biomedical Optics and Imaging}, volume = {5}, pages = {371-379}, note = {Fei, BW Muzic, RF Lee, Z Flask, CA Morris, RL Duerk, JL Oleinick, N Wilson, DL Medical Imaging 2004 Conference Feb 17-19, 2004 San Diego, CA SPIE, Amer Assoc Phys Med, Amer Physiol Soc, Ctr Devices & Radiol Hlth, Soc Imaging Sci & Technol, Natl Elect Mfg Assoc, Diagnost Imaging & Therapy Syst Div, Radiol Soc N Amer, Soc Comp Applicat Radiol}, abstract = {We are investigating imaging techniques to study the rapid biochemical and physiological response of tumors to photodynamic therapy (PDT). Positron emission tomography (PET) can provide physiological and functional images of cancers. While MRI can provide high resolution anatomical images and generate serial, noninvasive, in vivo observations of morphological changes. In this study, we investigate image registration methods to combine MRI and micro-PET (muPET) images for improved tumor monitoring. We acquired high resolution MR and PET (18)F-fluorodeoxyglucose (FDG) images from mice with RIF-1 tumors. We used rigid body registration with three translations and three angular variables. We used normalized mutual information as the similarity measure. To assess the quality of 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 of the organs. We also used visual inspection techniques such as color overlay displays. Over 40 volume registration experiments were performed with MR and muPET images acquired from three C3H mice. The color overlays showed that the MR images and the PET images matched well. The distance between corresponding centroids of organs was 1.5 +/- 0.4 mm which is about 2 pixels of muPET. In conclusion, registration of high resolution MR and muPET images of mice may be useful to combine anatomical and functional information that could be used for the potential application in photodynamic therapy.}, year = {2004} } @article{ author = {Fei, B. W. and Ng, W. S. and Chauhan, S. and Kwoh, C. K.}, title = {The safety issues of medical robotics}, journal = {Reliability Engineering & System Safety}, volume = {73}, number = {2}, pages = {183-192}, note = {Fei, BW Ng, WS Chauhan, S Kwoh, CK}, abstract = {In this paper, we put forward a systematic method to analyze, control and evaluate the safety issues of medical robotics. We created a safety model that consists of three axes to analyze safety factors. Software and hardware are the two material axes. The third axis is the policy that controls all phases of design, production, testing and application of the robot system. The policy was defined as hazard identification and safety insurance control (HISIC) that includes seven principles: definitions and requirements, hazard identification, safety insurance control, safety critical limits, monitoring and control, verification and validation, system log and documentation. HISIC was implemented in the development of a robot for urological applications that was known as URObot. The URObot is a universal robot with different modules adaptable for 3D ultrasound image-guided interstitial laser coagulation, radiation seed implantation, laser resection, and electrical resection of the prostate. Safety was always the key issue in the building of the robot. The HISIC strategies were adopted for safety enhancement in mechanical, electrical and software design. The initial test on URObot showed that HISIC had the potential ability to improve the safety of the system. Further safety experiments are being conducted in our laboratory. (C) 2001 Elsevier Science Ltd. All rights reserved.}, year = {2001} } @inbook{ author = {Fei, B. W. and Ng, W. S. and Kwoh, C. K.}, title = {The hazard identification & safety insurance control (HISIC) for medical robot}, booktitle = {Proceedings of the 22nd Annual International Conference of the Ieee Engineering in Medicine and Biology Society, Vols 1-4}, editor = {Enderle, J. D.}, series = {Proceedings of Annual International Conference of the Ieee Engineering in Medicine and Biology Society}, volume = {22}, pages = {3022-3026}, note = {Fei, BW Ng, WS Kwoh, CK 22nd Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society Jul 23-28, 2000 Chicago, il IEEE, Engn Med & Biol Soc, Amer Assoc Physicists Med, Amer Inst Med & Biol Engn, Int Union Phys & Engn Sci Med, Int Federat Med & Biol Engn, Int Org Med Phys}, abstract = {A novel systematic methodology for the enhancement of safety of medical robot, in terms of hazard identification gr safety insurance control (HISIC), is put forward in this paper. HISIC is tea identify, evaluate, and control medical safety hazards based on seven principles: definitions and requirements, hazard identification, safety insurance control, safety critical limits, monitoring and control, verification & validation, system log and documentation, HISIC tries to provide a standard for the safety off medical robot. Its initial implementation in a robot for urological application named URObot was successful, URObot in our lab is a universal platform for 3D ultrasound image-guided interstitial laser coagulation (ILC), radiation seed implantation (RSI) and laser resection (LR) to treat the benign prostate hyperplasia (BPH) and prostate cancer. URObot is currently undergoing safety test HISIC improves URObot safety.}, year = {2000} } @inbook{ author = {Fei, B. W. 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}, booktitle = {Medical Imaging 2012: Image-Guided Procedures, Robotic Interventions, and Modeling}, editor = {Holmes, D. R. and Wong, K. H.}, series = {Proceedings of SPIE}, volume = {8316}, note = {Fei, Baowei Schuster, David M. Master, Viraj Akbari, Hamed Fenster, Aaron Nieh, Peter Conference on Medical Imaging - Image-Guided Procedures, Robotic Interventions and Modeling Feb 05-07, 2012 San Diego, CA SPIE, Agillent Technol, Diamond SA, DQE Instruments Inc, eMagin, Isuzu Glass Co Ltd, Medtron Inc, Ocean Thin Films Inc}, 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.}, year = {2012} } @article{ author = {Fei, B. W. 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 in Surgery and Medicine}, volume = {39}, number = {9}, pages = {723-730}, note = {Fei, Baowei Wang, Hesheng Meyers, Joseph D. Feyes, Denise K. Oleinick, Nancy L. Duerk, Jeffrey L.}, 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/CM2). 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.}, year = {2007} } @inbook{ author = {Fei, B. W. and Wang, H. S. and Muzic, R. F. and Flask, C. A. and Feyes, D. K. and Wilson, D. L. and Duerk, J. L. and Oleinick, N. L.}, title = {Finite element model-based tumor registration of microPET and high-resolution MR images for photodynamic therapy in mice - art. no. 61433I}, booktitle = {Medical Imaging 2006: Physiology, Function, and Structure from Medical Images Pts 1 and 2}, editor = {Manduca, A. and Amini, A. A.}, series = {Proceedings of the Society of Photo-Optical Instrumentation Engineers (Spie)}, volume = {6143}, pages = {I1433-I1433}, note = {Fei, Baowei Wang, Hesheng Muzic, Raymond F., Jr. Flask, Chris A. Feyes, Denise K. Wilson, David L. Duerk, Jeffrey L. Oleinick, Nancy L. Medical Imaging 2006 Conference Feb 12-14, 2006 San Diego, CA Spie}, abstract = {We are investigating imaging techniques to study the tumor response to photodynamic therapy (PDT). PET can provide physiological and functional information. High-resolution 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 [F-18]fluorodeoxyglucose (FDG) images from C3H mice with RIF-1 tumors that were treated with Pc 4-based PDT. For tumor registration, we developed a finite element model (FEM)-based deformable registration scheme. To assess the registration quality, we performed slice by slice review of both image volumes, computed the volume overlap ratios, and visualized both volumes in color overlay. The mean volume overlap ratios for tumors were 94.7% after registration. 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.}, year = {2006} } @article{ author = {Fei, B. W. and Wang, H. S. and Muzic, R. F. 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 = {Medical Physics}, volume = {33}, number = {3}, pages = {753-760}, note = {Fei, BW Wang, HS Muzic, RF Flask, C Wilson, DL Duerk, JL Feyes, DK Oleinick, NL}, 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 F-18-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. (c) 2006 American Association of Physicists in Medicine.}, year = {2006} } @article{ author = {Fei, B. W. and Wang, H. S. and Muzic, R. F. 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 = {Medical Physics}, volume = {33}, number = {3}, pages = {753-760}, note = {Fei, BW Wang, HS Muzic, RF Flask, C Wilson, DL Duerk, JL Feyes, DK Oleinick, NL}, 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 F-18-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. (c) 2006 American Association of Physicists in Medicine.}, year = {2006} } @article{ author = {Fei, B. W. and Wang, H. S. and Wu, C. Y. and Chiu, S. M.}, title = {Choline PET for Monitoring Early Tumor Response to Photodynamic Therapy}, journal = {Journal of Nuclear Medicine}, volume = {51}, number = {1}, pages = {130-138}, note = {Fei, Baowei Wang, Hesheng Wu, Chunying Chiu, Song-mao}, 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 C-11-choline were acquired before PDT and at 1, 24, and 48 h after PDT. Time-activity curves of C-11-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 C-11-choline uptake in PDT-treated and control cells were measured. Results: For treated tumors, normalized C-11-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 C-11-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% C-11-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 C-11-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.}, year = {2010} } @article{ author = {Fei, B. W. and Wheaton, A. and Lee, Z. H. and Duerk, J. L. and Wilson, D. L.}, title = {Automatic MR volume registration and its evaluation for the pelvis and prostate}, journal = {Physics in Medicine and Biology}, volume = {47}, number = {5}, pages = {823-838}, note = {Fei, BW Wheaton, A Lee, ZH Duerk, JL Wilson, DL}, 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 0 for Man. 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.}, year = {2002} } @inbook{ author = {Fei, B. W. and Wheaton, A. and Lee, Z. and Nagano, K. and Duerk, J. L. and Wilson, D. L.}, title = {Robust registration method for interventional MRI-guided thermal ablation of prostate cancer}, booktitle = {Medical Imaging 2001: Visualization, Display, and Image-Guided Procedures}, editor = {Mun, S. K.}, series = {Proceedings of the Society of Photo-Optical Instrumentation Engineers (Spie)}, volume = {2}, pages = {53-60}, note = {Fei, BW Wheaton, A Lee, Z Nagano, K Duerk, JL Wilson, DL Medical Imaging 2001 Conference Feb 18-22, 2001 San diego, ca SPIE, Amer Assoc Physicists Med, Amer Physiol Soc, FDA Ctr Devices & Radiol Hlth, Soc Imaging Sci & Technol, Natl Elect Manufacturers Assoc, Diagnost Imaging & Therapy Syst Div, Radiol Soc N Amer, Soc Comp Applicat Radiol}, abstract = {We are investigating methods to register live-time interventional magnetic resonance imaging (iMRI) slice images with a previously obtained, high resolution MRI image volume. The immediate application is for iMRI-guided treatments of prostate cancer. We created and evaluated a slice-to-volume mutual information registration algorithm for MR images with special features to improve robustness. Features included a multi-resolution approach and automatic restarting to avoid local minima. We acquired 3D volume images from a 1.5 T MRI system and simulated iMRI images. To assess the quality of registration, we calculated 3D displacement on a voxel-by-voxel basis over a volume of interest between slice-to-volume registration and volume-to-volume registrations that were previously shown to be quite accurate. More than 500 registration experiments were performed on MR images of volunteers. The slice-to-volume registration algorithm was very robust for transverse slice images covering the prostate. A 100% success rate was achieved with an acceptance criterion of < 1.0 mm displacement error over the prostate. Our automatic slice-to-volume mutual information registration algorithm is robust and probably sufficiently accurate to aid in the application of iMRI-guided thermal ablation of prostate cancer.}, year = {2001} } @inbook{ author = {Fei, B. W. and Wietholt, C. and Clough, A. V. and Dawson, C. A. and Wilson, D. L. and Ieee}, title = {Automatic registration and fusion of high resolution micro-CT and lung perfusion SPECT images of the rat}, booktitle = {Proceedings of the 25th Annual International Conference of the Ieee Engineering in Medicine and Biology Society, Vols 1-4: A New Beginning for Human Health}, series = {Proceedings of Annual International Conference of the Ieee Engineering in Medicine and Biology Society}, volume = {25}, pages = {592-594}, note = {Fei, BW Wietholt, C Clough, AV Dawson, CA Wilson, DL 25th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society Sep 17-21, 2003 Cancun, MEXICO IEEE Engn Med & Biol Soc, Coral, Univ Autonome Metropolitana, Sandia Natl Lab}, abstract = {Small animal imaging can provide high-throughput phenotypic data for functional genomic studies and better mechanistic understanding of disease. Fusion of anatomical and functional images will aid interpretation of functional images having relatively little anatomical detail. In this study, we are investigating automatic registration and fusion visualization methods for micro-CT and SPECT images of rat lung. The immediate application is studies of pulmonary perfusion in a healthy rat and one with an occluded left pulmonary artery. Registration experiments were performed on images acquired from rats and a phantom. Fusion visualization showed excellent registration results. Quantitative measures such as distances and perimeters from phantom results show that the registration is quite accurate.}, year = {2003} } @inbook{ author = {Fei, B. W. and Zhang, S. X. and Savado, O. and Suri, J. and Lewin, J. S. and Wilson, D. L. and Ieee}, title = {Three-dimensional automatic volume registration of carotid MR images}, booktitle = {Proceedings of the 25th Annual International Conference of the Ieee Engineering in Medicine and Biology Society, Vols 1-4: A New Beginning for Human Health}, series = {Proceedings of Annual International Conference of the Ieee Engineering in Medicine and Biology Society}, volume = {25}, pages = {646-648}, note = {Fei, BW Zhang, SX Savado, O Suri, J Lewin, JS Wilson, DL 25th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society Sep 17-21, 2003 Cancun, MEXICO IEEE Engn Med & Biol Soc, Coral, Univ Autonome Metropolitana, Sandia Natl Lab}, abstract = {We created an automatic three-dimensional registration algorithm for magnetic resonance images of carotid vessels. Potential 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 measurement of disease progression and regression with drug trials. We used mutual information registration algorithm 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 1.09 +/- 0.42 mm.}, year = {2003} } @inbook{ author = {Fei, B. W. and Zhuang, T. G. and Hu, J. and Zhou, F. M.}, title = {Frameless stereotactic localization and multimodal image registration using DSA/CT/MRI}, booktitle = {Proceedings of the 20th Annual International Conference of the Ieee Engineering in Medicine and Biology Society, Vol 20, Pts 1-6: Biomedical Engineering Towards the Year 2000 and Beyond}, editor = {Chang, H. K. and Zhang, Y. T.}, series = {Proceedings of Annual International Conference of the Ieee Engineering in Medicine and Biology Society}, volume = {20}, pages = {683-685}, note = {Fei, BW Zhuang, TG Hu, J Zhou, FM 10th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society Oct 29-nov 01, 1998 Hong kong, peoples r china IEEE Engn Med & Biol Soc}, abstract = {In this paper, a novel frameless stereotactic localization method and multimodal image registration techniques for computer assisted surgery are presented. Using four external markers, the position of brain tissue can be calculated by two different DSA projection images, CT slices and MRI slices respectively. The different anatomical information (tone, soft tissue and vessel) obtained from CT, MRI and DSA can be registered together, Using DSA, the locating accuracy of phantom experiment is 0.5mm the accuracy of skull experiment is 2.0mm. The registration accuracy of DSA/CT images of skull is 2.0-2.5mm. The volumetric representation of registered DSA and MRI images of human head shows satisfying results.}, year = {1998} } @inbook{ 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 = {In vivo small animal imaging for early assessment of therapeutic efficacy of photodynamic therapy for prostate cancer - art. no. 651102}, booktitle = {Medical Imaging 2007: Physiology, Function, and Structure from Medical Images}, editor = {Manduca, A. and Hu, X. P.}, series = {Proceedings of the Society of Photo-Optical Instrumentation Engineers (Spie)}, volume = {6511}, pages = {51102-51102}, note = {Fei, Baowei Wang, Hesheng Chen, Xiang Meyers, Joseph Mulvihill, John Feyes, Denise Edgehouse, Nancy Duerk, Jeffrey L. Pretlow, Thomas G. Oleinick, Nancy L. Medical Imaging 2007 Conference Feb 18-20, 2007 San Diego, CA SPIE, Amer Assoc Physicists, Amer Physiol Soc, Comp Assisted Radiol & Surg, Soc Imaging Sci & Technol, Med Image Percept Soc, Radiol Soc N Amer, Soc Imaging Informat Med, Soc Mole Imaging, DICOM Standards Comm}, 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 highfield 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.}, year = {2007} } @article{ author = {Feng, S. S. J. and Bliznakova, K. and Qin, X. and Fei, B. and Sechopoulos, I.}, title = {Characterization of the Homogeneous Breast Tissue Mixture Approximation for Breast Image Dosimetry}, journal = {Medical Physics}, volume = {39}, number = {6}, pages = {3878-3878}, note = {Feng, S. S. J. Bliznakova, K. Qin, X. Fei, B. Sechopoulos, I. 54th Annual Meeting and Exhibition of the American-Association-of-Physicists-in-Medicine (AAPM) Jul 29-aug 02, 2012 Charlotte, NC Amer Assoc Physicists Med (AAPM)}, year = {2012} } @article{ author = {Haaga, J. R. and Exner, A. and Fei, B. W. and Seftel, A. D.}, title = {Semiquantitative imaging measurement of baseline and vasomodulated normal prostatic blood flow using sildenafil}, journal = {International Journal of Impotence Research}, volume = {19}, number = {1}, pages = {110-113}, note = {Haaga, J. R. Exner, A. Fei, B. W. Seftel, A. D.}, 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.}, year = {2007} } @book{ author = {Hwang, M. J. and Bebek, O. and Liang, F. and Fei, B. W. and Cavusoglu, M. C. and Ieee}, title = {Kinematic Calibration of a Parallel Robot for Small Animal Biopsies}, series = {2009 Ieee-Rsj International Conference on Intelligent Robots and Systems}, note = {Hwang, Myun Joong Bebek, Ozkan Liang, Fan Fei, Baowei Cavusoglu, M. Cenk IEEE RSJ International Conference on Intelligent Robots and Systems Oct 10-15, 2009 St Louis, MO IEEE Robot & Automat Soc (RA), Robot Soc Japan (RSJ), Soc Instruments & Control Engn, IEEE Ind Elect Soc, Inst Control, Robot & Syst Korea, ABB, Barrett Technol, Inc, Willow Garage, ROBOTIS, Aldebaran Robot}, abstract = {In biomedical research it is difficult to perceive tumors or cells and perform biopsies manually. Robotics technology can offer a reliable solution for accurate needle insertion. A novel 5 degrees of freedom (DOF) robot for inserting needles into small animal subjects was developed. The robot can realize dexterous alignment of the needle using two parallel mechanisms, and has a syringe mechanism to insert needles to subjects. Operations on small animals require high accuracy positioning during needle insertion. In this paper, kinematic calibration of the 5 DOF robot using an optical tracker as an e:Eternal sensor is performed to enhance accuracy of the system.}, pages = {4104-4109}, year = {2009} } @inbook{ author = {Li, K. and Fei, B. W.}, title = {A deformable model-based minimal path segmentation method for kidney MR images - art. no. 69144F}, booktitle = {Medical Imaging 2008: Image Processing, Pts 1-3}, editor = {Reinhardt, J. M. and Pluim, J. P. W.}, series = {Proceedings of the Society of Photo-Optical Instrumentation Engineers (Spie)}, volume = {6914}, pages = {F9144-F9144}, note = {Li, Ke Fei, Baowei Medical Imaging 2008 Conference Feb 17-19, 2008 San Diego, CA SPIE, Amer Assoc Phys Med, Amer Physiol Soc, Comp Assisted Radiol & Surg, Soc Imaging Sci & Technol, Med Image Percept Soc, Radiol Soc N Amer, Soc Imaging Informat Med, Soc Mole Imaging, DICOM Standards Comm}, 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.}, year = {2008} } @article{ author = {MacDonald, T. and Liu, J. B. and Munson, J. and Park, J. and Wang, K. and Fei, B. W. and Bellamkonda, R. and Arbiser, J.}, title = {THE APPLICATION OF NANOPARTICLE LIPOSOME-IMPRAMINE BLUE IN THE TREATMENT OF MEDULLOBLASTOMA IN THE SmoA1 TRANSGENIC MICE}, journal = {Neuro-Oncology}, volume = {14}, pages = {83-83}, note = {MacDonald, Tobey Liu, Jingbo Munson, Jenny Park, Jaekeun Wang, Kenty Fei, Baowei Bellamkonda, Ravi Arbiser, Jack 15th International Symposium on Pediatric Neuro-Oncology (ISPNO) Jun 24-27, 2012 Toronto, CANADA 1}, year = {2012} } @article{ author = {Mafi, J. N. and Fei, B. W. and Roble, S. and Dota, A. and Katrapati, P. and Bezerra, H. G. and Wang, H. S. 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 = {Journal of Digital Imaging}, volume = {25}, number = {1}, pages = {129-136}, 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.}, 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 (13 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.}, year = {2012} } @article{ author = {Schuster, D. and Fei, B. and Fox, T. and Osunkoya, A. O.}, title = {Histopathologic Correlation of Prostatic Adenocarcinoma on Radical Prostatectomy with Pre-Operative Anti-18F Fluorocyclobutyl-Carboxylic Acid Positron Emission Tomography/Computed Tomography}, journal = {Modern Pathology}, volume = {24}, pages = {222A-223A}, note = {Schuster, D. Fei, B. Fox, T. Osunkoya, A. O. 100th Annual Meeting United States-and-Canadian-Academy-of-Pathology Feb 26-mar 04, 2011 San Antonio, TX United States Canadian Acad Pathol 1}, year = {2011} } @article{ author = {Schuster, D. and Fei, B. and Fox, T. and Osunkoya, A. O.}, title = {Histopathologic Correlation of Prostatic Adenocarcinoma on Radical Prostatectomy with Pre-Operative Anti-18F Fluorocyclobutyl-Carboxylic Acid Positron Emission Tomography/Computed Tomography}, journal = {Laboratory Investigation}, volume = {91}, pages = {222A-223A}, note = {Schuster, D. Fei, B. Fox, T. Osunkoya, A. O. 100th Annual Meeting of the United States and Canadian-Academy-of-Pathology Feb 26-mar 04, 2011 San Antonio, TX Canadian Acad Pathol 1}, year = {2011} } @article{ author = {Sechopoulos, I. and Bliznakova, K. and Qin, X. L. and Fei, B. W. and Feng, S. S. J.}, title = {Characterization of the homogeneous tissue mixture approximation in breast imaging dosimetry}, journal = {Medical Physics}, volume = {39}, number = {8}, pages = {5050-5059}, note = {Sechopoulos, Ioannis Bliznakova, Kristina Qin, Xulei Fei, Baowei Feng, Steve Si Jia}, 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. 0 2012 American Association of Physicists in Medicine. [http://dx.doi.org/10.1118/1.4737025]}, year = {2012} } @book{ author = {Suri, J. and Pappu, V. and Salvado, O. and Fei, B. W. and Zhang, S. X. and Lewin, J. and Duerk, J. and Wilson, D.}, title = {Rotational effect on ROI's for accurate lumen quantification in bifurcated MR plaque volumes}, series = {17th Ieee Symposium on Computer-Based Medical Systems, Proceedings}, note = {Suri, J Pappu, V Salvado, O Fei, BW Zhang, SX Lewin, J Duerk, J Wilson, D 17th IEEE Symposium on Computer-Based Medical Systems Jun 24-25, 2004 Bethesda, MD IEEEComp Soc, tccm, Texas Tech Univ Coll Engn}, abstract = {This paper presents a use of geometric-based method integrated with classifier for lumen wall estimation using MR plaque volumes. The following are the new things the readers will observe when it comes to plaque imaging. (a) Application of three different sets of classifiers (Fuzzy, Maxkovian and Graph-based) for lumen region classification in plaque MR volumes. These classifiers axe used in multi-resolution framework. (b) Usage of rule-based region merging applied to the sub-classes of lumen region. (c) Rotational effect on region of interest in arterial bifurcation zones for accurate lumen region identification and boundary estimation. We have used our diagnostic system with three different classifying methods on actual patient data. We measure performance of the system by computing the mean distance error with respect to boundaries traced manually by human experts. Overall, the system consists of 22,500 boundary points. The in-plane pixel resolution is 0.25 millimeters. Using Markovian classifier method, the average error was 0.61 pixels; using Fuzzy classifier method, the average error was 0.62 pixels; using Graph-based classifier method, the average error was 0.74 pixels. All these methods lead to error less than 0.185 mm. We also validated our system by simulating the lumen images with additive Gaussian perturbations. This system works on a Linux platform and is written in C++.}, pages = {414-418}, year = {2004} } @article{ author = {Wang, H. S. and Fei, B. W.}, 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}, 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. (C) 2008 Elsevier B.V. All rights reserved.}, year = {2009} } @article{ author = {Wang, H. S. and Fei, B. W.}, title = {Diffusion-Weighted MRI for Monitoring Tumor Response to Photodynamic Therapy}, journal = {Journal of Magnetic Resonance Imaging}, volume = {32}, number = {2}, pages = {409-417}, note = {Wang, Hesheng Fei, Baowei}, 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.}, year = {2010} } @article{ author = {Wang, H. S. and Fei, B. W.}, title = {An MR image-guided, voxel-based partial volume correction method for PET images}, journal = {Medical Physics}, volume = {39}, number = {1}, pages = {179-194}, note = {Wang, Hesheng Fei, Baowei}, 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 mu ci/cc for cerebrospinal fluid (CSF), 228 mu ci/cc for white matter (WM), and 621 mu ci/cc for gray matter (GM), the method has improved the radioactivity quantification from 186 +/- 16 mu ci/cc to 30 +/- 7 mu ci/cc in CSF, 317 +/- 15 mu ci/cc to 236 +/- 10 mu ci/cc for WM, 438 +/- 4 mu ci/ cc to 592 +/- 5 mu ci/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. (C) 2012 American Association of Physicists in Medicine. [DOI: 10.1118/1.3665704]}, year = {2012} } @inbook{ author = {Wang, H. S. and Feyes, D. and Mulvihill, J. and Oleinick, N. and MacLennan, G. and Fei, B. W.}, title = {Multiscale fuzzy C-means image classification for multiple weighted MR images for the assessment of photodynamic therapy in mice - art. no. 65122W}, booktitle = {Medical Imaging 2007: Image Processing, Pts 1-3}, editor = {Pluim, J. P. W. and Reinhardt, J. M.}, series = {Proceedings of the Society of Photo-Optical Instrumentation Engineers (Spie)}, volume = {6512}, pages = {W5122-W5122}, note = {Wang, Hesheng Feyes, Denise Mulvihill, John Oleinick, Nancy MacLennan, Gregory Fei, Baowei Medical Imaging 2007 Conference Feb 18-20, 2007 San Diego, CA SPIE, Amer Assoc Physicists, Amer Physiol Soc, Comp Assisted Radiol & Surg, Soc Imaging Sci & Technol, Med Image Percept Soc, Radiol Soc N Amer, Soc Imaging Informat Med, Soc Mole Imaging, DICOM Standards Comm}, 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.}, year = {2007} } @inbook{ author = {Yang, X. F. and Akbari, H. and Halig, L. and Fei, B. W.}, title = {3D Non-rigid Registration Using Surface and Local Salient Features for Transrectal Ultrasound Image-guided Prostate Biopsy}, booktitle = {Medical Imaging 2011: Visualization, Image-Guided Procedures, and Modeling}, editor = {Wong, K. H. and Holmes, D. R.}, series = {Proceedings of SPIE}, volume = {7964}, note = {Yang, Xiaofeng Akbari, Hamed Halig, Luma Fei, Baowei Conference on Medical Imaging 2011 - Visualization, Image-Guided Procedures, and Modeling Feb 13-15, 2011 Lake Buena Vista, FL SPIE, Dynasil Corp/RMD Res, AAPM - Amer Assoc Physicists Med, DQE Instruments, Inc, Ocean Thin Films, Inc, Univ Cent Florida, CREOL - Coll Opt & Photon, VIDA Diagnost, Inc}, 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 mm(3) for all five patients. The experimental results demonstrate the robustness and accuracy of the 3D non-rigid registration algorithm.}, year = {2011} } @inbook{ author = {Yang, X. F. and Fei, B. W.}, title = {A Skull Segmentation Method for Brain MR Images Based on Multiscale Bilateral Filtering Scheme}, booktitle = {Medical Imaging 2010: Image Processing}, editor = {Dawant, B. M. and Haynor, D. R.}, series = {Proceedings of SPIE}, volume = {7623}, note = {Yang, Xiaofeng Fei, Baowei Conference on Medical Imaging 2010 - Image Processing Feb 14-16, 2010 San Diego, CA SPIE, Medtronic, Inc., Aeroflex, Inc., OpenXi, Tungsten Heavy Powder, Inc.}, abstract = {We present a novel automatic segmentation method for the skull on brain MR images for attenuation correction in combined PET/MRI applications. Our method transforms T1-weighted MR images to the Radon domain and then detects the feature of the skull. In the Radon domain we use a bilateral filter to construct a multiscale images series. For the repeated convolution we increase the spatial smoothing at each scale and make the cumulative width of the spatial and range Gaussian doubled at 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 method is robust for noise MR images because of its multiscale bilateral filtering scheme. After combining the two filtered sinogram, the reciprocal binary sinogram of the skull is obtained for the reconstruction of the skull image. We use the filtered back projection method to reconstruct the segmented skull image. We define six metrics to evaluate our segmentation method. The method has been tested with brain phantom data, simulated brain data, and real MRI data. Evaluation results showed that our method is robust and accurate, which is useful for skull segmentation and subsequently for attenuation correction in combined PET/MRI applications.}, year = {2010} } @article{ author = {Yang, X. F. and Fei, B. W.}, title = {A multiscale and multiblock fuzzy C-means classification method for brain MR images}, journal = {Medical Physics}, volume = {38}, number = {6}, pages = {2879-2891}, note = {Yang, Xiaofeng Fei, Baowei}, 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. (C) 2011 American Association of Physicists in Medicine. [DOI: 10.1118/1.3584199]}, year = {2011} } @article{ author = {Yang, X. F. and Fei, B. W.}, title = {A wavelet multiscale denoising algorithm for magnetic resonance (MR) images}, journal = {Measurement Science & Technology}, volume = {22}, number = {2}, note = {Yang, Xiaofeng Fei, Baowei}, 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.}, year = {2011} } @inbook{ author = {Yang, X. F. and Fei, B. W.}, title = {3D Prostate Segmentation of Ultrasound Images Combining Longitudinal Image Registration and Machine Learning}, booktitle = {Medical Imaging 2012: Image-Guided Procedures, Robotic Interventions, and Modeling}, editor = {Holmes, D. R. and Wong, K. H.}, series = {Proceedings of SPIE}, volume = {8316}, note = {Yang, Xiaofeng Fei, Baowei Conference on Medical Imaging - Image-Guided Procedures, Robotic Interventions and Modeling Feb 05-07, 2012 San Diego, CA SPIE, Agillent Technol, Diamond SA, DQE Instruments Inc, eMagin, Isuzu Glass Co Ltd, Medtron Inc, Ocean Thin Films Inc}, 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.}, year = {2012} } @inbook{ author = {Yang, X. F. and Ghafourian, P. and Sharma, P. and Salman, K. and Martin, D. and Fei, B. W.}, title = {Nonrigid Registration and Classification of the Kidneys in 3D Dynamic Contrast Enhanced (DCE) MR Images}, booktitle = {Medical Imaging 2012: Image Processing}, editor = {Haynor, D. R. and Ourselin, S.}, series = {Proceedings of SPIE}, volume = {8314}, note = {Yang, Xiaofeng Ghafourian, Pegah Sharma, Puneet Salman, Khalil Martin, Diego Fei, Baowei Conference on Medical Imaging - Image Processing Feb 06-09, 2012 San Diego, CA SPIE, Agilent Technol, Diamond SA, DQE Instruments Inc, eMagin, Isuzu Glass Co Ltd, Medtron Inc, Ocean Thin Films Inc}, 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.}, year = {2012} } @inbook{ author = {Yang, X. F. and Schuster, D. and Master, V. and Nieh, P. and Fenster, A. and Fei, B. W.}, title = {Automatic 3D Segmentation of Ultrasound Images Using Atlas Registration and Statistical Texture Prior}, booktitle = {Medical Imaging 2011: Visualization, Image-Guided Procedures, and Modeling}, editor = {Wong, K. H. and Holmes, D. R.}, series = {Proceedings of SPIE}, volume = {7964}, note = {Yang, Xiaofeng Schuster, David Master, Viraj Nieh, Peter Fenster, Aaron Fei, Baowei Conference on Medical Imaging 2011 - Visualization, Image-Guided Procedures, and Modeling Feb 13-15, 2011 Lake Buena Vista, FL SPIE, Dynasil Corp/RMD Res, AAPM - Amer Assoc Physicists Med, DQE Instruments, Inc, Ocean Thin Films, Inc, Univ Cent Florida, CREOL - Coll Opt & Photon, VIDA Diagnost, Inc}, 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.}, year = {2011} } @inbook{ author = {Yang, X. F. and Sechopoulos, I. and Fei, B. W.}, title = {Automatic Tissue Classification for High-resolution Breast CT Images Based on Bilateral Filtering}, booktitle = {Medical Imaging 2011: Image Processing}, editor = {Dawant, B. M. and Haynor, D. R.}, series = {Proceedings of SPIE}, volume = {7962}, note = {Yang, Xiaofeng Sechopoulos, Ioannis Fei, Baowei Conference on Medical Imaging 2011 - Image Processing Feb 14-16, 2011 Lake Buena Vista, FL Dynasil Corp/RMD Res, Amer Assoc Physicists Med, DQE Instruments Inc, Ocean Thin Films, Inc, Univ Cent Florida, CREOL - Coll Opt & Photon, VIDA Diagnost, Inc, SPIE}, 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.}, year = {2011} } @inbook{ author = {Zhang, H. M. and Bian, Z. Z. and Gu, Y. M. and Fei, B. W. and Ye, M. and Ieee}, title = {An efficient multiscale approach to level set evolution}, booktitle = {Proceedings of the 25th Annual International Conference of the Ieee Engineering in Medicine and Biology Society, Vols 1-4: A New Beginning for Human Health}, series = {Proceedings of Annual International Conference of the Ieee Engineering in Medicine and Biology Society}, volume = {25}, pages = {694-697}, note = {Zhang, HM Bian, ZZ Gu, YM Fei, BW Ye, M 25th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society Sep 17-21, 2003 Cancun, MEXICO IEEE Engn Med & Biol Soc, Coral, Univ Autonome Metropolitana, Sandia Natl Lab}, abstract = {In this paper, an efficient multiscale scheme for level set evolution is proposed. First, we are addressing the problem of passing the solution from the coarser scale to the finer one. Inspired by the idea of the entropy condition and its extention, an efficient passing solution method is presented, where neither extrapolation nor complex computation is needed. Thus it could induce fast convergence rate. Furthermore, an improved Hermes algorithm, called fast Hermes, is developed to fast implement the level set evolution on each scale by further loosening the constraint in the intermediate levels. Our approach is evaluated and compared to the existing algorithm. The experimental results are very promising.}, year = {2003} }