TY - CONF AU - Fei, Baowei AU - Zhuang, Tiange AU - Hu, Jie AU - Zhou, Fanmin PB - IEEE PY - 1998 SN - 0780351649 SP - 683-685 ST - Frameless stereotactic localization and multimodal image registration using DSA/CT/MRI T2 - Engineering in Medicine and Biology Society, 1998. Proceedings of the 20th Annual International Conference of the IEEE TI - Frameless stereotactic localization and multimodal image registration using DSA/CT/MRI VL - 2 ID - 122 ER - TY - CONF AU - Fei, BW AU - Kwoh, CK AU - Ng, WS PB - IEEE PY - 1999 SN - 0780356748 SP - 896 vol. 2 ST - The software design for a medical robot for urological applications T2 - [Engineering in Medicine and Biology, 1999. 21st Annual Conference and the 1999 Annual Fall Meetring of the Biomedical Engineering Society] BMES/EMBS Conference, 1999. Proceedings of the First Joint TI - The software design for a medical robot for urological applications VL - 2 ID - 131 ER - TY - CONF AU - Khan, Liaquat A AU - Fei, BW AU - Ng, WS AU - Kwoh, CK PB - IEEE PY - 1999 SN - 0780356748 SP - 649 vol. 1 ST - X-ray localization technique for total hip replacement operation in augmented reality for therapy (ART) T2 - [Engineering in Medicine and Biology, 1999. 21st Annual Conference and the 1999 Annual Fall Meetring of the Biomedical Engineering Society] BMES/EMBS Conference, 1999. Proceedings of the First Joint TI - X-ray localization technique for total hip replacement operation in augmented reality for therapy (ART) VL - 1 ID - 147 ER - TY - CONF AU - Fei, Baowei AU - Ng, Wan Sing AU - Kwoh, Chee Keong PB - IEEE PY - 2000 SN - 0780364651 SP - 3022-3026 ST - The hazard identification and safety insurance control (HISIC) for medical robot T2 - Engineering in Medicine and Biology Society, 2000. Proceedings of the 22nd Annual International Conference of the IEEE TI - The hazard identification and safety insurance control (HISIC) for medical robot VL - 4 ID - 123 ER - TY - CPAPER AU - Kahn, LA AU - Fei, Baowei AU - Ng, WS AU - Kwoh, CK CY - Philadelphia, PA DA - June 3-6 PY - 2000 T2 - The 17th Symposium for Computer Applications in Radiology, Section A-Digital Imaging TI - The image intensifier (II) distortion calibration method in X-ray localization for total hip replacement (THR) ID - 347 ER - TY - CONF AU - Fei, Baowei AU - Wheaton, Andrew AU - Lee, Zhenghong AU - Nagano, Kenichi AU - Duerk, Jeffrey L AU - Wilson, David L PY - 2001 SP - 53-60 ST - Robust registration method for interventional MRI-guided thermal ablation of prostate cancer T2 - Proc. SPIE TI - Robust registration method for interventional MRI-guided thermal ablation of prostate cancer VL - 4319 ID - 110 ER - TY - CONF AU - Fei, BW AU - Boll, Daniel T AU - Duerk, Jeffery L AU - Wilson, David L PY - 2002 SP - 1185 ST - Image registration for interventional MRI-guided minimally invasive treatment of prostate cancer T2 - The 2nd Joint Meeting of the IEEE Engineering in Medicine and Biology Society and the Biomedical Engineering Society TI - Image registration for interventional MRI-guided minimally invasive treatment of prostate cancer VL - 2 ID - 126 ER - TY - CONF AU - Fei, B AU - Kemper, C AU - Wilson, DL M1 - 1 PB - International Society for Optical Engineering; 1999 PY - 2002 SN - 0361-0748 SP - 528-537 ST - Three-dimensional warping registration of the pelvis and prostate [4684-55] T2 - PROCEEDINGS-SPIE THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING TI - Three-dimensional warping registration of the pelvis and prostate [4684-55] ID - 162 ER - TY - CONF AU - Fei, Baowei AU - Frinkley, Kristin AU - Wilson, David L PY - 2003 SN - 0819448303 SP - 192-201 ST - Registration algorithms for interventional MRI-guided treatment of the prostate T2 - Proceedings of SPIE TI - Registration algorithms for interventional MRI-guided treatment of the prostate VL - 5029 ID - 142 ER - TY - CONF AU - Fei, Baowei AU - Wietholt, Christian AU - Clough, Anne V AU - Dawson, Christopher A AU - Wilson, David L PB - IEEE PY - 2003 SN - 0780377893 SP - 592-594 ST - Automatic registration and fusion of high resolution micro-CT and lung perfusion SPECT images of the rat T2 - Engineering in Medicine and Biology Society, 2003. Proceedings of the 25th Annual International Conference of the IEEE TI - Automatic registration and fusion of high resolution micro-CT and lung perfusion SPECT images of the rat VL - 1 ID - 164 ER - TY - CONF AU - Fei, Baowei AU - Zhang, Shaoxiong AU - Savado, Olivier AU - Suri, Jasjit AU - Lewin, Jonathan S AU - Wilson, David L PB - IEEE PY - 2003 SN - 0780377893 SP - 646-648 ST - Three-dimensional automatic volume registration of carotid MR images T2 - Engineering in Medicine and Biology Society, 2003. Proceedings of the 25th Annual International Conference of the IEEE TI - Three-dimensional automatic volume registration of carotid MR images VL - 1 ID - 115 ER - TY - CHAP A2 - Ellis, R. E. A2 - Peters, T. M. AB - 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. AN - WOS:000188180400045 AU - Fei, B. W. AU - Lee, Z. H. AU - Boll, D. T. AU - Duerk, J. L. AU - Lewin, J. S. AU - Wilson, D. L. N1 - Times Cited: 18 6th International Conference on Medical Image Computing and Computer-Assisted Intervention NOV 15-18, 2003 MONTREAL, CANADA Robarts Res Inst; No Digital Inc Lewin, Jonathan/A-4331-2009; Fei, Baowei /E-6898-2014 Fei, Baowei /0000-0002-9123-9484 0 18 PY - 2003 SN - 0302-9743 3-540-20464-4 SP - 364-372 ST - Image registration and fusion for interventional MRI guided thermal ablation of the prostate cancer T2 - Medical Image Computing and Computer-Assisted Intervention - Miccai 2003, Pt 2 T3 - Lecture Notes in Computer Science TI - Image registration and fusion for interventional MRI guided thermal ablation of the prostate cancer UR - ://WOS:000188180400045 VL - 2879 ID - 295 ER - TY - CHAP A2 - Gee, J. C. A2 - Maintz, J. B. A. A2 - Vannier, M. W. AB - 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. AN - WOS:000187954800034 AU - Fei, B. W. AU - Lee, Z. H. AU - Duerk, J. L. AU - Wilson, D. L. N1 - Times Cited: 10 2nd International Workshop on Biomedical Image Registration JUN 23-24, 2003 Univ Penn, PHILADELPHIA, PA Siemens Med Solut; Siemens Corp Res; Natl Lib Med; Univ Penn, Vice Provost Res Fei, Baowei /E-6898-2014 Fei, Baowei /0000-0002-9123-9484 0 10 PY - 2003 SN - 0302-9743 3-540-20343-5 SP - 321-329 ST - Image registration for interventional MRI guided procedures: Interpolation methods, similarity measurements, and applications to the prostate T2 - Biomedical Image Registration T3 - Lecture Notes in Computer Science TI - Image registration for interventional MRI guided procedures: Interpolation methods, similarity measurements, and applications to the prostate UR - ://WOS:000187954800034 VL - 2717 ID - 296 ER - TY - JOUR AU - White, Lee AU - Fei, Baowei PY - 2003 ST - Failures of GUI Tests on Different Computer Platforms T2 - ISSRE 2003 Fast Abstract TI - Failures of GUI Tests on Different Computer Platforms ID - 219 ER - TY - CONF AU - Zhang, Hongmei AU - Bian, Zhengzhong AU - Guo, Youmin AU - Fei, Baowei AU - Ye, Min PB - IEEE PY - 2003 SN - 0780377893 SP - 694-697 ST - An efficient multiscale approach to level set evolution T2 - Engineering in Medicine and Biology Society, 2003. Proceedings of the 25th Annual International Conference of the IEEE TI - An efficient multiscale approach to level set evolution VL - 1 ID - 109 ER - TY - JOUR AU - Fei, Baowei AU - Muzic, R AU - Lee, Zhenghong AU - Flask, C AU - Morris, R AU - Duerk, Jeffery L AU - Wilson, DL PY - 2004 SP - 371-379 ST - Registration of micro-PET and high resolution MR images of mice for monitoring photodynamic therapy T2 - Proceeding of SPIE on Medical Imaging: Physiology, Function, and Structure from Medical Images TI - Registration of micro-PET and high resolution MR images of mice for monitoring photodynamic therapy ID - 121 ER - TY - CONF AN - WOS:000222998000069 AU - Suri, J AU - Pappu, V AU - Salvado, O AU - Fei, BW AU - Zhang, SX AU - Lewin, J AU - Duerk, J AU - Wilson, D AU - Long, R AU - Antani, S AU - Lee, DJ AU - Nutter, B AU - Zhang, M DA - 2004 PY - 2004 SP - 414-418 ST - Rotational effect on ROI's for accurate lumen quantification in bifurcated MR plaque volumes T2 - Proceedings of 17th IEEE Symposium on Computer-Based Medical Systems TI - Rotational effect on ROI's for accurate lumen quantification in bifurcated MR plaque volumes ID - 346 ER - TY - CONF AU - Fei, Baowei AU - Duerk, JL AU - Wilson, DL AU - Oleinick, NL CY - Washington, DC DA - Oct 27-29, 2005 PB - US Congress PY - 2005 ST - Multimodality Molecular Imaging for Potential Applications of Image-Guided Treatment for Prostate Cancer: Thermal Ablation and Photodynamic Therapy T2 - The 3rd International Public Conference of the AdMeTech Foundation TI - Multimodality Molecular Imaging for Potential Applications of Image-Guided Treatment for Prostate Cancer: Thermal Ablation and Photodynamic Therapy ID - 345 ER - TY - JOUR AB - In vivo small animal imaging provides a powerful tool for the study of a variety of diseases. Magnetic resonance imaging (MRI) has become an established technology for the assessment of therapies. In this study, we used high-resolution MRI to evaluate polycystic kidney disease (PKD) in transgenic mice. We used a customized mouse coil to acquire serial MR images from both wide-type and transgenic PKD mice immediately prior to, and 2-week and 4-week after therapy. We developed image segmentation, registration and visualization methods for this novel imaging application. We measured the kidney volumes for each mouse to assess the efficacy of the therapy. The segmentation results show that the kidney volumes are consistent, which are 348.7 ± 19.7 mm3for wild-type mice and 756.3 ± 44.1 mm3for transgenic mice, respectively. The image analysis methods provide a useful tool for this new application. AD - Department of Radiology, Case Western Reserve University & University Hospitals of Cleveland, USA. AN - 17282217 AU - Fei, B. AU - Flask, C. AU - Wang, H. AU - Pi, A. AU - Wilson, D. AU - Shillingford, J. AU - Murcia, N. AU - Weimbs, T. AU - Duerk, J. DO - 10.1109/IEMBS.2005.1616448 [doi] DP - Nlm ET - 2007/02/07 LA - eng N1 - Fei, Baowei Flask, Chris Wang, Hesheng Pi, Ai Wilson, David Shillingford, Jonathan Murcia, Noel Weimbs, Thomas Duerk, Jeffrey R01 CA084433/CA/NCI NIH HHS/United States R01 DK062338/DK/NIDDK NIH HHS/United States United States Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference Conf Proc IEEE Eng Med Biol Soc. 2005;1:467-9. PY - 2005 SN - 1557-170X (Print) 1557-170X (Linking) SP - 467-9 ST - Image Segmentation, Registration and Visualization of Serial MR Images for Therapeutic Assessment of Polycystic Kidney Disease in Transgenic Mice T2 - Conf Proc IEEE Eng Med Biol Soc TI - Image Segmentation, Registration and Visualization of Serial MR Images for Therapeutic Assessment of Polycystic Kidney Disease in Transgenic Mice UR - http://ieeexplore.ieee.org/document/1616448/ VL - 1 ID - 86 ER - TY - JOUR AB - We are investigating image processing and analysis techniques to improve the ability of dual-energy digital radiography (DR) for the detection of cardiac calcification. Computed tomography (CT) is an established tool for the diagnosis of coronary artery diseases. Dual-energy digital radiography could be a cost-effective alternative. In this study, we use three-dimensional (3D) CT images as the "gold standard" to evaluate the DR X-ray images for calcification detection. To this purpose, we developed an automatic registration method for 3D CT volumes and two-dimensional (2D) X-ray images. We call this 3D-to-2D registration. We first use a 3D CT image volume to simulate X-ray projection images and then register them with X-ray images. The registered CT projection images are then used to aid the interpretation dual-energy X-ray images for the detection of cardiac calcification. We acquired both CT and X-ray images from patients with coronary artery diseases. Experimental results show that the 3D-to-2D registration is accurate and useful for this new application. AD - Dept. of Radiol. & Biomed. Eng., Case Western Reserve Univ., Cleveland, OH 44106, USA. baowei.fei@case.edu AN - 17945687 AU - Fei, B. AU - Chen, X. AU - Wang, H. AU - Sabol, J. M. AU - DuPont, E. AU - Gilkeson, R. C. C2 - 2743908 DO - 10.1109/IEMBS.2006.259888 [doi] DP - Nlm ET - 2007/10/20 KW - Algorithms Artificial Intelligence Calcinosis/diagnostic imaging Coronary Angiography/ methods Coronary Artery Disease/ diagnostic imaging Humans Imaging, Three-Dimensional/ methods Lung Diseases/diagnostic imaging Radiographic Image Enhancement/ methods Radiography, Dual-Energy Scanned Projection/ methods Reproducibility of Results Sensitivity and Specificity Subtraction Technique Tomography, X-Ray Computed/ methods L1 - internal-pdf://0308537105/Fei-2006-Automatic registration of CT volumes.pdf LA - eng N1 - Fei, Baowei Chen, Xiang Wang, Hesheng Sabol, John M DuPont, Elena Gilkeson, Robert C R21 CA120536/CA/NCI NIH HHS/United States R21 CA120536-01/CA/NCI NIH HHS/United States R21CA120536/CA/NCI NIH HHS/United States Evaluation Studies Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't United States Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference Nihms113523 Conf Proc IEEE Eng Med Biol Soc. 2006;1:1976-9. PY - 2006 SN - 1557-170X (Print) 1557-170X (Linking) SP - 1976-9 ST - Automatic registration of CT volumes and dual-energy digital radiography for detection of cardiac and lung diseases T2 - Conf Proc IEEE Eng Med Biol Soc TI - Automatic registration of CT volumes and dual-energy digital radiography for detection of cardiac and lung diseases UR - https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2743908/pdf/nihms-113523.pdf VL - 1 ID - 82 ER - TY - CONF AU - Fei, Baowei AU - Wang, Hesheng AU - Muzic Jr, Raymond F AU - Flask, Chris A AU - Feyes, Denise AU - Wilson, David L AU - Duerk, Jeffrey L AU - Oleinick, Nancy L PB - International Society for Optics and Photonics PY - 2006 SP - 61433I-61433I-10 ST - Finite element model-based tumor registration of microPET and high-resolution MR images for photodynamic therapy in mice T2 - Medical Imaging TI - Finite element model-based tumor registration of microPET and high-resolution MR images for photodynamic therapy in mice ID - 145 ER - TY - CONF AU - Greer, M AU - Azar, N AU - Faulhber, PP AU - Fei, B CY - Chicago, IL DA - October 11-14, 2006 PY - 2006 ST - Molecular Imaging for Improved Detection of Gynecologic Cancer- Image Registration and Fusion Visualization T2 - The 2006 Biomedical Engineering Society Annual Meeting TI - Molecular Imaging for Improved Detection of Gynecologic Cancer- Image Registration and Fusion Visualization ID - 344 ER - TY - CONF AU - McKinley, ET AU - Heinzel, EM AU - Johnson, DH AU - Roy, D AU - Steyer, GJ AU - Fei, Baowei AU - Wilson, DL CY - Chicago, IL DA - Oct 11-14, 2006 PY - 2006 ST - High Resolution Magnetic Resonance and Cryo-Imaging for Morphological Phenotyping T2 - The 2006 Biomedical Engineering Society Annual Meeting TI - High Resolution Magnetic Resonance and Cryo-Imaging for Morphological Phenotyping ID - 342 ER - TY - JOUR AB - We are investigating three-dimensional (3D) to two-dimensional (2D) registration methods for computed tomography (CT) and dual-energy digital radiography (DR) for the detection of coronary artery calcification. CT is an established tool for the diagnosis of coronary artery diseases (CADs). Dual-energy digital radiography could be a cost-effective alternative for screening coronary artery calcification. In order to utilize CT as the "gold standard" to evaluate the ability of DR images for the detection and localization of calcium, we developed an automatic intensity-based 3D-to-2D registration method for 3D CT volumes and 2D DR images. To generate digital rendering radiographs (DRR) from the CT volumes, we developed three projection methods, i.e. Gaussian-weighted projection, threshold-based projection, and average-based projection. We tested normalized cross correlation (NCC) and normalized mutual information (NMI) as similarity measurement. We used the Downhill Simplex method as the search strategy. Simulated projection images from CT were fused with the corresponding DR images to evaluate the localization of cardiac calcification. The registration method was evaluated by digital phantoms, physical phantoms, and clinical data sets. The results from the digital phantoms show that the success rate is 100% with mean errors of less 0.8 mm and 0.2 degree for both NCC and NMI. The registration accuracy of the physical phantoms is 0.34 +/- 0.27 mm. Color overlay and 3D visualization of the clinical data show that the two images are registered well. This is consistent with the improvement of the NMI values from 0.20 +/- 0.03 to 0.25 +/- 0.03 after registration. The automatic 3D-to-2D registration method is accurate and robust and may provide a useful tool to evaluate the dual-energy DR images for the detection of coronary artery calcification. AD - Case Western Reserve University and Xi'an Jiaotong University. University Hospitals Case Medical Center. Case Western Reserve University. AN - 24386527 AU - Chen, X. AU - Gilkeson, R. AU - Fei, B. C2 - 3877237 DA - Mar 03 DO - 10.1117/12.710192 [doi] DP - Nlm ET - 2007/03/03 LA - eng N1 - Chen, Xiang Gilkeson, Robert Fei, Baowei R21 CA120536/CA/NCI NIH HHS/United States United States Proceedings of SPIE--the International Society for Optical Engineering Nihms432054 Proc SPIE Int Soc Opt Eng. 2007 Mar 3;6512. doi: 10.1117/12.710192. PY - 2007 SN - 0277-786X (Print) 0277-786X (Linking) ST - Automatic Intensity-based 3D-to-2D Registration of CT Volume and Dual-energy Digital Radiography for the Detection of Cardiac Calcification T2 - Proc SPIE Int Soc Opt Eng TI - Automatic Intensity-based 3D-to-2D Registration of CT Volume and Dual-energy Digital Radiography for the Detection of Cardiac Calcification UR - https://www.spiedigitallibrary.org/conference-proceedings-of-spie/6512/1/Automatic-intensity-based-3D-to-2D-registration-of-CT-volume/10.1117/12.710192.short?SSO=1 VL - 6512 ID - 85 ER - TY - CONF AU - Fei, Baowei AU - Azar, N AU - Greer, M AU - Rochon, PJ AU - Faulhaber, PP CY - New York, NY DA - March 15-18, 2007 PY - 2007 ST - Automatic Registration and Fusion of Ultrasound Imaging and Positron Emission Tomography (PET) for Improved Diagnosis of Gynecologic Cancer T2 - The American Institute of Ultrasound in Medicine 2007 Convention TI - Automatic Registration and Fusion of Ultrasound Imaging and Positron Emission Tomography (PET) for Improved Diagnosis of Gynecologic Cancer ID - 340 ER - TY - CONF AU - Fei, Baowei AU - Duerk, JL AU - Oleinick, NL CY - Atlanta, Georgia DA - Sep. 5-8, 2007 PY - 2007 ST - Multimodality Molecular Imaging for Photodynamic Therapy of Prostate Cancer T2 - US Department of Defense Prostate Cancer Research Program- The Innovative Minds in Prostate Cancer Today (IMPaCT) Inaugural Meeting TI - Multimodality Molecular Imaging for Photodynamic Therapy of Prostate Cancer ID - 341 ER - TY - JOUR AB - We are developing in vivo small animal imaging techniques that can measure early effects of photodynamic therapy (PDT) for prostate cancer. PDT is an emerging therapeutic modality that continues to show promise in the treatment of cancer. At our institution, a new second-generation photosensitizing drug, the silicon phthalocyanine Pc 4, has been developed and evaluated at the Case Comprehensive Cancer Center. In this study, we are developing magnetic resonance imaging (MRI) techniques that provide therapy monitoring and early assessment of tumor response to PDT. We generated human prostate cancer xenografts in athymic nude mice. For the imaging experiments, we used a high-field 9.4-T small animal MR scanner (Bruker Biospec). High-resolution MR images were acquired from the treated and control tumors pre- and post-PDT and 24 hr after PDT. We utilized multi-slice multi-echo (MSME) MR sequences. During imaging acquisitions, the animals were anesthetized with a continuous supply of 2% isoflurane in oxygen and were continuously monitored for respiration and temperature. After imaging experiments, we manually segmented the tumors on each image slice for quantitative image analyses. We computed three-dimensional T2 maps for the tumor regions from the MSME images. We plotted the histograms of the T2 maps for each tumor pre- and post-PDT and 24 hr after PDT. After the imaging and PDT experiments, we dissected the tumor tissues and used the histologic slides to validate the MR images. In this study, six mice with human prostate cancer tumors were imaged and treated at the Case Center for Imaging Research. The T2 values of treated tumors increased by 24 +/- 14% 24 hr after the therapy. The control tumors did not demonstrate significant changes of the T2 values. Inflammation and necrosis were observed within the treated tumors 24 hour after the treatment. Preliminary results show that Pc 4-PDT is effective for the treatment of human prostate cancer in mice. The small animal MR imaging provides a useful tool to evaluate early tumor response to photodynamic therapy in mice. AD - Department of Radiology, Case Western Reserve University, University Hospitals of Cleveland, and the Case Comprehensive Cancer Center ; Department of Biomedical Engineering, Case Western Reserve University, University Hospitals of Cleveland, and the Case Comprehensive Cancer Center. Department of Biomedical Engineering, Case Western Reserve University, University Hospitals of Cleveland, and the Case Comprehensive Cancer Center. Department of Radiology, Case Western Reserve University, University Hospitals of Cleveland, and the Case Comprehensive Cancer Center. Department of Radiation Oncology, Case Western Reserve University, University Hospitals of Cleveland, and the Case Comprehensive Cancer Center. Department of Pathology, Case Western Reserve University, University Hospitals of Cleveland, and the Case Comprehensive Cancer Center. AN - 24386525 AU - Fei, B. AU - Wang, H. AU - Chen, X. AU - Meyers, J. AU - Mulvihill, J. AU - Feyes, D. AU - Edgehouse, N. AU - Duerk, J. L. AU - Pretlow, T. G. AU - Oleinick, N. L. C2 - 3877221 DA - Mar 29 DO - 10.1117/12.708718 [doi] DP - Nlm ET - 2007/03/29 LA - eng N1 - Fei, Baowei Wang, Hesheng Chen, Xiang Meyers, Joseph Mulvihill, John Feyes, Denise Edgehouse, Nancy Duerk, Jeffrey L Pretlow, Thomas G Oleinick, Nancy L R21 CA120536/CA/NCI NIH HHS/United States R24 CA110943/CA/NCI NIH HHS/United States United States Proceedings of SPIE--the International Society for Optical Engineering Nihms432056 Proc SPIE Int Soc Opt Eng. 2007 Mar 29;6511. doi: 10.1117/12.708718. PY - 2007 SN - 0277-786X (Print) 0277-786X (Linking) ST - In Vivo Small Animal Imaging for Early Assessment of Therapeutic Efficacy of Photodynamic Therapy for Prostate Cancer T2 - Proc SPIE Int Soc Opt Eng TI - In Vivo Small Animal Imaging for Early Assessment of Therapeutic Efficacy of Photodynamic Therapy for Prostate Cancer UR - https://www.spiedigitallibrary.org/conference-proceedings-of-spie/6511/1/In-vivo-small-animal-imaging-for-early-assessment-of-therapeutic/10.1117/12.708718.short VL - 6511 ID - 83 ER - TY - JOUR AB - We are investigating in vivo small animal imaging and analysis methods for the assessment of photodynamic therapy (PDT), an emerging therapeutic modality for cancer treatment. Multiple weighted MR images were acquired from tumor-bearing mice pre- and post-PDT and 24-hour after PDT. We developed an automatic image classification method to differentiate live, necrotic and intermediate tissues within the treated tumor on the MR images. We used a multiscale diffusion filter to process the MR images before classification. A multiscale fuzzy C-means (FCM) classification method was applied along the scales. The object function of the standard FCM was modified to allow multiscale classification processing where the result from a coarse scale is used to supervise the classification in the next scale. The multiscale fuzzy C-means (MFCM) method takes noise levels and partial volume effects into the classification processing. The method was validated by simulated MR images with various noise levels. For simulated data, the classification method achieved 96.0 +/- 1.1% overlap ratio. For real mouse MR images, the classification results of the treated tumors were validated by histologic images. The overlap ratios were 85.6 +/- 5.1%, 82.4 +/- 7.8% and 80.5 +/- 10.2% for the live, necrotic, and intermediate tissues, respectively. The MR imaging and the MFCM classification methods may provide a useful tool for the assessment of the tumor response to photodynamic therapy in vivo. AD - Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, 44106. Department of Radiation Oncology, Case Western Reserve University, Cleveland, OH, 44106. Department of Pathology, Case Western Reserve University, Cleveland, OH, 44106. Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, 44106 ; Department of Radiology Case Western Reserve University, Cleveland, OH, 44106. AN - 24386526 AU - Wang, H. AU - Feyes, D. AU - Mulvihill, J. AU - Oleinick, N. AU - Maclennan, G. AU - Fei, B. C2 - 3877232 DA - Mar 08 DO - 10.1117/12.710188 [doi] DP - Nlm ET - 2007/03/08 LA - eng N1 - Wang, Hesheng Feyes, Denise Mulvihill, John Oleinick, Nancy Maclennan, Gregory Fei, Baowei R21 CA120536/CA/NCI NIH HHS/United States R24 CA110943/CA/NCI NIH HHS/United States United States Proceedings of SPIE--the International Society for Optical Engineering Nihms432055 Proc SPIE Int Soc Opt Eng. 2007 Mar 8;6512. doi: 10.1117/12.710188. PY - 2007 SN - 0277-786X (Print) 0277-786X (Linking) ST - Multiscale Fuzzy C-Means Image Classification for Multiple Weighted MR Images for the Assessment of Photodynamic Therapy in Mice T2 - Proc SPIE Int Soc Opt Eng TI - Multiscale Fuzzy C-Means Image Classification for Multiple Weighted MR Images for the Assessment of Photodynamic Therapy in Mice UR - https://www.spiedigitallibrary.org/conference-proceedings-of-spie/6512/1/Multiscale-fuzzy-C-means-image-classification-for-multiple-weighted-MR/10.1117/12.710188.short VL - 6512 ID - 84 ER - TY - JOUR AB - Small animals are widely used in biomedical research studies. They have compact anatomy and small organs. Therefore it is difficult to perceive tumors or cells and perform biopsies manually. Robotics technology offers a convenient and reliable solution for accurate needle insertion. In this paper, a novel 5 degrees of freedom (DOF) robot design for inserting needles into small animal subjects is proposed. The design has a compact size, is light weight, and has high resolution. Parallel mechanisms are used in the design for stable and reliable operation. The proposed robot has two gimbal joints that carry the needle mechanism. The robot can realize dexterous alignment of the needle before insertion. AD - Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, Ohio, 44106, USA. oxb6@case.edu AN - 19163987 AU - Bebek, O. AU - Hwang, M. J. AU - Fei, B. AU - Cavusoglu, M. C2 - 2796956 DO - 10.1109/IEMBS.2008.4650484 [doi] DP - Nlm ET - 2009/01/24 KW - Biopsy/ instrumentation/methods/ veterinary Equipment Design Equipment Failure Analysis Needles/ veterinary Reproducibility of Results Robotics/ instrumentation/methods Sensitivity and Specificity Surgery, Computer-Assisted/ instrumentation/methods L1 - internal-pdf://3037231223/Bebek-2008-Design of a small animal biopsy rob.pdf LA - eng N1 - Bebek, Ozkan Hwang, Myun Joong Fei, Baowei Cavusoglu, M R21 CA120536/CA/NCI NIH HHS/United States R21 CA120536-01/CA/NCI NIH HHS/United States R21 CA120536-02/CA/NCI NIH HHS/United States Evaluation Studies Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S. United States Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference Nihms113528 Conf Proc IEEE Eng Med Biol Soc. 2008;2008:5601-4. doi: 10.1109/IEMBS.2008.4650484. PY - 2008 SN - 1557-170X (Print) 1557-170X (Linking) SP - 5601-4 ST - Design of a small animal biopsy robot T2 - Conf Proc IEEE Eng Med Biol Soc TI - Design of a small animal biopsy robot UR - https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2796956/pdf/nihms113528.pdf VL - 2008 ID - 73 ER - TY - JOUR AB - At our institution, we are using dual-energy digital radiography (DEDR) as a cost-effective screening tool for the detection of cardiac calcification. We are evaluating DEDR using CT as the gold standard. We are developing image projection methods for the generation of digitally reconstructed radiography (DRR) from CT image volumes. Traditional visualization methods include maximum intensity projection (MIP) and average-based projection (AVG) that have difficulty to show cardiac calcification. Furthermore, MIP can over estimate the calcified lesion as it displays the maximum intensity along the projection rays regardless of tissue types. For AVG projection, the calcified tissue is usually overlapped with bone, lung and mediastinum. In order to improve the visualization of calcification on DRR images, we developed a Gaussian-weighted projection method for this particular application. We assume that the CT intensity values of calcified tissues have a Gaussian distribution. We then use multiple Gaussian functions to fit the intensity histogram. Based on the mean and standard deviation parameters, we incorporate a Gaussian weighted function into the perspective projection and display the calcification exclusively. Our digital and physical phantom studies show that the new projection method can display tissues selectively. In addition, clinical images show that the Gaussian-weighted projection method better visualizes cardiac calcification than either the AVG or MIP method and can be used to evaluate DEDR as a screening tool for the detection of coronary artery diseases. AD - Case Western Reserve University and Xi'an Jiaotong University. Case Western Reserve University. University Hospitals Case Medical Center. AN - 24386529 AU - Chen, X. AU - Li, K. AU - Gilkeson, R. AU - Fei, B. C2 - 3877249 DA - Mar 15 DO - 10.1117/12.772597 [doi] DP - Nlm ET - 2008/03/15 LA - eng N1 - Chen, Xiang Li, Ke Gilkeson, Robert Fei, Baowei R21 CA120536/CA/NCI NIH HHS/United States R24 CA110943/CA/NCI NIH HHS/United States U24 CA110943/CA/NCI NIH HHS/United States United States Proceedings of SPIE--the International Society for Optical Engineering Nihms432049 Proc SPIE Int Soc Opt Eng. 2008 Mar 15;6918. doi: 10.1117/12.772597. PY - 2008 SN - 0277-786X (Print) 0277-786X (Linking) ST - Gaussian Weighted Projection for Visualization of Cardiac Calcification T2 - Proc SPIE Int Soc Opt Eng TI - Gaussian Weighted Projection for Visualization of Cardiac Calcification UR - https://www.spiedigitallibrary.org/conference-proceedings-of-spie/6918/1/Gaussian-weighted-projection-for-visualization-of-cardiac-calcification/10.1117/12.772597.short VL - 6918 ID - 78 ER - TY - JOUR AU - Fei, Baowei AU - Wang, Hesheng AU - Wu, Chunying AU - Meyers, Joseph IS - supplement 1 PY - 2008 SN - 0161-5505 SP - 329P-329P ST - Choline molecular imaging with PET for photodynamic therapy of cancer T2 - Journal of Nuclear Medicine TI - Choline molecular imaging with PET for photodynamic therapy of cancer VL - 49 ID - 207 ER - TY - CONF AU - Li, Ke AU - Fei, Baowei PB - IEEE PY - 2008 SN - 1424417481 SP - 2342-2344 ST - A new 3D model-based minimal path segmentation method for kidney MR images T2 - Bioinformatics and Biomedical Engineering, 2008. ICBBE 2008. The 2nd International Conference on TI - A new 3D model-based minimal path segmentation method for kidney MR images ID - 119 ER - TY - CONF AU - Li, Ke AU - Fei, Baowei PB - NIH Public Access PY - 2008 ST - A deformable model-based minimal path segmentation method for kidney MR images T2 - Proceedings of SPIE TI - A deformable model-based minimal path segmentation method for kidney MR images VL - 6914 ID - 132 ER - TY - CONF AU - Wang, Hesheng AU - Fei, Baowei PB - IEEE PY - 2008 SN - 1424417481 SP - 2353-2356 ST - A robust B-Splines-based point match method for non-rigid surface registration T2 - Bioinformatics and Biomedical Engineering, 2008. ICBBE 2008. The 2nd International Conference on TI - A robust B-Splines-based point match method for non-rigid surface registration ID - 140 ER - TY - CONF AU - Ciancibello, L AU - Gilkeson, R AU - Fei, B M1 - 5 PB - AMER ROENTGEN RAY SOC 1891 PRESTON WHITE DR, SUBSCRIPTION FULFILLMENT, RESTON, VA 22091 USA PY - 2009 SN - 0361-803X ST - Bismuth Breast Shielding and its Effect on Calcium Score and Dose T2 - AMERICAN JOURNAL OF ROENTGENOLOGY TI - Bismuth Breast Shielding and its Effect on Calcium Score and Dose VL - 192 ID - 191 ER - TY - CONF AB - This study is to develop multimodality imaging (PET/MRI) as an early biomarker for monitoring tumor response to photodynamic therapy (PDT) at the cellular and tissue levels. Methods: A human prostate cancer cell line (CWR22) was used to generate tumors in athymic nude mice. A second-generation photosensitizing drug Pc 4 (0.6 mg/kg body weight) was delivered to each animal by tail vein injection 48 h before laser illumination (672 nm, 100 mW/cm2 , 150 J/cm2 ). For Group I (N=5), dynamic microPET images with 11C-choline were acquired from each mouse pre-PDT and 24 h and 48 h after PDT. For Group II (N=18), diffusion-weighted MR images were acquired pre- and post-PDT, 24 h, and/or 7 d after PDT. Apparent diffusion coefficient (ADC) maps were obtained and analyzed for each tumor. Prostate specific antigen (PSA) levels were measured 1 d before PDT and 24 h and 7 d after PDT. Results: The PSA values decreased by 30.3% and 64.1% 24 h and 7 d after PDT, respectively, indicating the treatment effect. For Group I, the choline uptakes dramatically decreased 24 h (75.5%) and 48 h (43.5%) after PDT, compared to those pre-PDT. Histologic analysis showed that PDT-treated tumors demonstrated apoptosis, necrosis and inflammation. For Group II, ADC values significantly increased (47.5%) 24 h after PDT. In four mice, the ADC histogram demonstrated a biphasic response 7 d after PDT, i.e. some tissue within the tumor had increased ADC values and other maintained approximately the same values as those before treatment. On MR images, tumor tissue was automatically classified into two tissue types (necrotic and viable), which were well correlated (R=89%) with tissue quantification from histology. The changes in choline uptake and ADC values are consistent with the PSA levels. Conclusions: Changes in tumor choline uptake detected by PET imaging can determine whether or not the tumor responds the therapy within 48 h after PDT. Diffusion-weighted MR imaging can detect and quantify viable and necrotic tumor tissue within one week after the treatment. The noninvasive imaging techniques can provide an assay that could be useful for clinical monitoring of photodynamic therapy at an early stage (1-7 days). AU - Fei, Baowei AU - Wang, Hesheng AU - Wu, Chunying AU - Chiu, Song-mao AU - Edgehouse, Nancy CY - Montreal, Canada DA - Sep. 23-26, 2009 PY - 2009 ST - Monitoring Tumor Cellular and Tissue Response to Photodynamic Therapy by Choline PET imaging and Diffusion-weighted MRI T2 - World Molecular Imaging Congress TI - Monitoring Tumor Cellular and Tissue Response to Photodynamic Therapy by Choline PET imaging and Diffusion-weighted MRI ID - 338 ER - TY - JOUR AB - We are developing and evaluating choline molecular imaging with positron emission tomography (PET) for monitoring tumor response to photodynamic therapy (PDT) in animal models. Human prostate cancer (PC-3) was studied in athymic nude mice. A second-generation photosensitizer Pc 4 was used for PDT in tumor-bearing mice. MicroPET images with (11)C-choline were acquired before PDT and 48 h after PDT. Time-activity curves of (11)C-choline uptake were analyzed before and after PDT. For treated tumors, normalized choline uptake decreased significantly 48 h after PDT, compared to the same tumors pre-PDT (p < 0.001). However, for the control tumors, normalized choline uptake increased significantly (p < 0.001). PET imaging with (11)C-choline is sensitive to detect early tumor response to PDT in the animal model of human prostate cancer. AD - Department of Radiology, Emory University, Atlanta, GA ; Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio. AN - 23336060 AU - Fei, B. AU - Wang, H. AU - Wu, C. AU - Meyers, J. AU - Xue, L. Y. AU - Maclennan, G. AU - Schluchter, M. C2 - 3546344 DO - 10.1117/12.812129 [doi] DP - Nlm ET - 2009/01/01 L1 - internal-pdf://2182586886/Fei-2009-Choline Molecular Imaging with Small-.pdf LA - eng N1 - Fei, Baowei Wang, Hesheng Wu, Chunying Meyers, Joseph Xue, Liang-Yan Maclennan, Gregory Schluchter, Mark R21 CA120536/CA/NCI NIH HHS/United States United States Proceedings of SPIE--the International Society for Optical Engineering Nihms432050 Proc SPIE Int Soc Opt Eng. 2009;7262:726211. Epub 2009 Feb 27. PY - 2009 SN - 0277-786X (Print) 0277-786X (Linking) SP - 726211 ST - Choline Molecular Imaging with Small-animal PET for Monitoring Tumor Cellular Response to Photodynamic Therapy of Cancer T2 - Proc SPIE Int Soc Opt Eng TI - Choline Molecular Imaging with Small-animal PET for Monitoring Tumor Cellular Response to Photodynamic Therapy of Cancer UR - https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3546344/pdf/nihms432050.pdf VL - 7262 ID - 74 ER - TY - JOUR AB - We are developing MRI-based attenuation correction methods for PET images. PET has high sensitivity but relatively low resolution and little anatomic details. MRI can provide excellent anatomical structures with high resolution and high soft tissue contrast. MRI can be used to delineate tumor boundaries and to provide an anatomic reference for PET, thereby improving quantitation of PET data. Combined PET/MRI can offer metabolic, functional and anatomic information and thus can provide a powerful tool to study the mechanism of a variety of diseases. Accurate attenuation correction represents an essential component for the reconstruction of artifact-free, quantitative PET images. Unfortunately, the present design of hybrid PET/MRI does not offer measured attenuation correction using a transmission scan. This problem may be solved by deriving attenuation maps from corresponding anatomic MR images. Our approach combines image registration, classification, and attenuation correction in a single scheme. MR images and the preliminary reconstruction of PET data are first registered using our automatic registration method. MRI images are then classified into different tissue types using our multiscale fuzzy C-mean classification method. The voxels of classified tissue types are assigned theoretical tissue-dependent attenuation coefficients to generate attenuation correction factors. Corrected PET emission data are then reconstructed using a three-dimensional filtered back projection method and an order subset expectation maximization method. Results from simulated images and phantom data demonstrated that our attenuation correction method can improve PET data quantitation and it can be particularly useful for combined PET/MRI applications. AD - Departments of Radiology, Emory University, Atlanta, GA. Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio. AN - 23682307 AU - Fei, B. AU - Yang, X. AU - Wang, H. C2 - 3653447 DA - Feb 27 DO - 10.1117/12.813755 [doi] DP - Nlm ET - 2009/02/27 LA - eng N1 - Fei, Baowei Yang, Xiaofeng Wang, Hesheng R21 CA120536/CA/NCI NIH HHS/United States United States Proceedings of SPIE--the International Society for Optical Engineering Nihms432051 Proc SPIE Int Soc Opt Eng. 2009 Feb 27;7262. pii: 726208. PY - 2009 SN - 0277-786X (Print) 0277-786X (Linking) ST - An MRI-based Attenuation Correction Method for Combined PET/MRI Applications T2 - Proc SPIE Int Soc Opt Eng TI - An MRI-based Attenuation Correction Method for Combined PET/MRI Applications UR - https://www.spiedigitallibrary.org/conference-proceedings-of-spie/7262/1/An-MRI-based-attenuation-correction-method-for-combined-PET-MRI/10.1117/12.813755.short VL - 7262 ID - 72 ER - TY - JOUR AB - We are developing a minimal path searching method for active shape model (ASM)-based segmentation for detection of lung boundaries on digital radiographs. With the conventional ASM method, the position and shape parameters of the model points are iteratively refined and the target points are updated by the least Mahalanobis distance criterion. We propose an improved searching strategy that extends the searching points in a fan-shape region instead of along the normal direction. A minimal path (MP) deformable model is applied to drive the searching procedure. A statistical shape prior model is incorporated into the segmentation. In order to keep the smoothness of the shape, a smooth constraint is employed to the deformable model. To quantitatively assess the ASM-MP segmentation, we compare the automatic segmentation with manual segmentation for 72 lung digitized radiographs. The distance error between the ASM-MP and manual segmentation is 1.75 +/- 0.33 pixels, while the error is 1.99 +/- 0.45 pixels for the ASM. Our results demonstrate that our ASM-MP method can accurately segment the lung on digital radiographs. AD - Quantitative BioImaging Laboratory, Department of Radiology, Emory University, Atlanta, GA 30322. AN - 24386531 AU - Guo, S. AU - Fei, B. C2 - 3877238 DA - Mar 27 DO - 10.1117/12.812575 [doi] DP - Nlm ET - 2009/03/27 LA - eng N1 - Guo, Shengwen Fei, Baowei R21 CA120536/CA/NCI NIH HHS/United States United States Proceedings of SPIE--the International Society for Optical Engineering Nihms432053 Proc SPIE Int Soc Opt Eng. 2009 Mar 27;7259. doi: 10.1117/12.812575. PY - 2009 SN - 0277-786X (Print) 0277-786X (Linking) ST - A Minimal Path Searching Approach for Active Shape Model (ASM)-based Segmentation of the Lung T2 - Proc SPIE Int Soc Opt Eng TI - A Minimal Path Searching Approach for Active Shape Model (ASM)-based Segmentation of the Lung UR - https://www.spiedigitallibrary.org/conference-proceedings-of-spie/7259/1/A-minimal-path-searching-approach-for-active-shape-model-ASM/10.1117/12.812575.short VL - 7259 ID - 70 ER - TY - CONF AU - Hwang, Myun Joong AU - Bebek, Ozkan AU - Liang, Fan AU - Fei, Baowei AU - Cavusoglu, M Cenk PB - IEEE PY - 2009 SN - 1424438039 SP - 4104-4109 ST - Kinematic calibration of a parallel robot for small animal biopsies T2 - Intelligent Robots and Systems, 2009. IROS 2009. IEEE/RSJ International Conference on TI - Kinematic calibration of a parallel robot for small animal biopsies ID - 120 ER - TY - CPAPER AU - Mafi, J. N. AU - Fei, Baowei AU - Gilkeson, R AU - Roble, S. AU - Dota, A. AU - Katrapati, P. AU - Bezerra, Hiram AU - Wang, Hesheng AU - Coletta, John AU - Wang, Wei AU - Ciancibello, L AU - Costa, M. AU - Simon, D. I. AU - Orringer, C. E. CY - Chicago, IL DA - Dec. 4, 2009 PY - 2009 T2 - RSNA Annual Meeting 2009, Session: Cardiac (CT Angiography: Dual Energy) TI - Quantification of Coronary Artery Calcium Using Dual-energy Subtraction Digital Radiography ID - 339 ER - TY - CONF AU - Wang, Hesheng AU - Fei, Baowei PB - NIH Public Access PY - 2009 ST - An MRI-guided PET partial volume correction method T2 - Proceedings of SPIE TI - An MRI-guided PET partial volume correction method VL - 7259 ID - 134 ER - TY - CONF AU - Fei, B AU - Yang, X AU - Nye, JA AU - Aasrsvold, JN AU - Meltzer, CC AU - Voltaw, JR CY - Knoxville, TN DA - Nov. 1, 2010 PY - 2010 ST - PET-MRI Qualification Tools- Registration, Segmentation, Classification, and Attenuation Correction T2 - IEEE Nuclear Science Symposium and Medical Imaging Conference - Focused Workshop on PET-MR TI - PET-MRI Qualification Tools- Registration, Segmentation, Classification, and Attenuation Correction ID - 343 ER - TY - JOUR AU - Fei, Baowei AU - Yang, Xiaofeng AU - Nye, Jonathon AU - Jones, Margie AU - Aarsvold, John AU - Raghunath, Nivedita AU - Meltzer, Carolyn AU - Votaw, John IS - supplement 2 PY - 2010 SN - 0161-5505 SP - 81-81 ST - MRI-based attenuation correction and quantification tools for combined MRI/PET T2 - Journal of Nuclear Medicine TI - MRI-based attenuation correction and quantification tools for combined MRI/PET VL - 51 ID - 186 ER - TY - CONF AU - Yang, Xiaofeng AU - Fei, Baowei PY - 2010 SP - 76233K ST - A skull segmentation method for brain MR images based on multiscale bilateral filtering scheme T2 - Medical Imaging: Image Processing TI - A skull segmentation method for brain MR images based on multiscale bilateral filtering scheme ID - 141 ER - TY - JOUR AB - The current definitive diagnosis of prostate cancer is transrectal ultrasound (TRUS) guided biopsy. However, the current procedure is limited by using 2D biopsy tools to target 3D biopsy locations. This paper presents a new method for automatic segmentation of the prostate in three-dimensional transrectal ultrasound images, by extracting texture features and by statistically matching geometrical shape of the prostate. A set of Wavelet-based support vector machines (W-SVMs) are located and trained at different regions of the prostate surface. The WSVMs capture texture priors of ultrasound images for classification of the prostate and non-prostate tissues in different zones around the prostate boundary. In the segmentation procedure, these W-SVMs are trained in three sagittal, coronal, and transverse planes. The pre-trained W-SVMs are employed to tentatively label each voxel around the surface of the model as a prostate or non-prostate voxel by the texture matching. The labeled voxels in three planes after post-processing is overlaid on a prostate probability model. The probability prostate model is created using 10 segmented prostate data. Consequently, each voxel has four labels: sagittal, coronal, and transverse planes and one probability label. By defining a weight function for each labeling in each region, each voxel is labeled as a prostate or non-prostate voxel. Experimental results by using real patient data show the good performance of the proposed model in segmenting the prostate from ultrasound images. AD - Department of Radiology, Emory University, 1841 Clifton Rd, NE, Atlanta, GA, USA 30329. AN - 22468205 AU - Akbari, H. AU - Yang, X. AU - Halig, L. V. AU - Fei, B. C2 - 3314427 DO - 10.1117/12.878072 [doi] DP - Nlm ET - 2011/01/01 L1 - internal-pdf://1935685926/Akbari-2011-3D Segmentation of Prostate Ultras.pdf LA - eng N1 - Akbari, Hamed Yang, Xiaofeng Halig, Luma V Fei, Baowei R01 CA156775-02/CA/NCI NIH HHS/United States R01 CA156775-01/CA/NCI NIH HHS/United States R01 CA156775-03/CA/NCI NIH HHS/United States R01 CA156775/CA/NCI NIH HHS/United States UL1 RR025008/RR/NCRR NIH HHS/United States P50 CA128301/CA/NCI NIH HHS/United States United States Proceedings of SPIE--the International Society for Optical Engineering Nihms362788 Proc SPIE Int Soc Opt Eng. 2011;7962:79622K. Epub 2011 Mar 14. PY - 2011 SN - 0277-786X (Print) 0277-786X (Linking) SP - 79622K ST - 3D Segmentation of Prostate Ultrasound images Using Wavelet Transform T2 - Proc SPIE Int Soc Opt Eng TI - 3D Segmentation of Prostate Ultrasound images Using Wavelet Transform UR - https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3314427/pdf/nihms362788.pdf VL - 7962 ID - 67 ER - TY - JOUR AB - Prostate cancer affects 1 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. AD - Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA 30329; Winship Cancer Institute, Emory University, Atlanta, GA 30329; Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA 30329. Department of Urology, Emory University, Atlanta, GA 30329. Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA 30329. Imaging Research Laboratories, Robarts Research Institute, London, Ontario, Canada, N6A 5K8. AN - 26866061 AU - Fei, B. AU - Master, V. AU - Nieh, P. AU - Akbari, H. AU - Yang, X. AU - Fenster, A. AU - Schuster, D. C2 - 4745094 DP - Nlm ET - 2011/01/01 LA - eng N1 - Fei, Baowei Master, Viraj Nieh, Peter Akbari, Hamed Yang, Xiaofeng Fenster, Aaron Schuster, David R21 CA176684/CA/NCI NIH HHS/United States R01 CA156775/CA/NCI NIH HHS/United States UL1 RR025008/RR/NCRR NIH HHS/United States P50 CA128301/CA/NCI NIH HHS/United States P50 CA128613/CA/NCI NIH HHS/United States Germany Prostate cancer imaging : image analysis and image-guided interventions : international workshop held in conjunction with MICCAI 2011, Toronto, Canada, September 22, 2011 : proceedings Nihms716010 Prostate Cancer Imaging (2011). 2011;6363:100-108. PY - 2011 SP - 100-108 ST - A PET/CT Directed, 3D Ultrasound-Guided Biopsy System for Prostate Cancer T2 - Prostate Cancer Imaging (2011) TI - A PET/CT Directed, 3D Ultrasound-Guided Biopsy System for Prostate Cancer VL - 6363 ID - 64 ER - TY - JOUR AN - WOS:000291285000379 AU - Schuster, D. AU - Fei, B. AU - Fox, T. AU - Osunkoya, A. O. DA - Feb N1 - Times Cited: 2 1 100th Annual Meeting of the United States and Canadian-Academy-of-Pathology FEB 26-MAR 04, 2011 San Antonio, TX Canadian Acad Pathol Schuster, David/D-6156-2011; Fei, Baowei /E-6898-2014 Fei, Baowei /0000-0002-9123-9484 0 2 PY - 2011 SN - 0023-6837 SP - 222A-223A ST - Histopathologic Correlation of Prostatic Adenocarcinoma on Radical Prostatectomy with Pre-Operative Anti-18F Fluorocyclobutyl-Carboxylic Acid Positron Emission Tomography/Computed Tomography T2 - Laboratory Investigation TI - Histopathologic Correlation of Prostatic Adenocarcinoma on Radical Prostatectomy with Pre-Operative Anti-18F Fluorocyclobutyl-Carboxylic Acid Positron Emission Tomography/Computed Tomography UR - ://WOS:000291285000379 VL - 91 ID - 309 ER - TY - JOUR AB - We present a 3D non-rigid registration algorithm for the potential use in combining PET/CT and transrectal ultrasound (TRUS) images for targeted prostate biopsy. Our registration is a hybrid approach that simultaneously optimizes the similarities from point-based registration and volume matching methods. The 3D registration is obtained by minimizing the distances of corresponding points at the surface and within the prostate and by maximizing the overlap ratio of the bladder neck on both images. The hybrid approach not only capture deformation at the prostate surface and internal landmarks but also the deformation at the bladder neck regions. The registration uses a soft assignment and deterministic annealing process. The correspondences are iteratively established in a fuzzy-to-deterministic approach. B-splines are used to generate a smooth non-rigid spatial transformation. In this study, we tested our registration with pre- and post-biopsy TRUS images of the same patients. Registration accuracy is evaluated using manual defined anatomic landmarks, i.e. calcification. The root-mean-squared (RMS) of the difference image between the reference and floating images was decreased by 62.6+/-9.1% after registration. The mean target registration error (TRE) was 0.88+/-0.16 mm, i.e. less than 3 voxels with a voxel size of 0.38x0.38x0.38 mm3 for all five patients. The experimental results demonstrate the robustness and accuracy of the 3D non-rigid registration algorithm. AD - Department of Radiology, Emory University. AN - 24027609 AU - Yang, X. AU - Akbari, H. AU - Halig, L. AU - Fei, B. C2 - 3766999 DA - Mar 01 DO - 10.1117/12.878153 [doi] DP - Nlm ET - 2011/03/01 L1 - internal-pdf://0460784861/Yang-2011-3D Non-rigid Registration Using Surf.pdf LA - eng N1 - Yang, Xiaofeng Akbari, Hamed Halig, Luma Fei, Baowei R01 CA156775-02/CA/NCI NIH HHS/United States R01 CA156775-01/CA/NCI NIH HHS/United States R01 CA156775-03/CA/NCI NIH HHS/United States R01 CA156775/CA/NCI NIH HHS/United States UL1 RR025008/RR/NCRR NIH HHS/United States P50 CA128301/CA/NCI NIH HHS/United States United States Proceedings of SPIE--the International Society for Optical Engineering Nihms362780 Proc SPIE Int Soc Opt Eng. 2011 Mar 1;7964:79642V. PY - 2011 SN - 0277-786X (Print) 0277-786X (Linking) SP - 79642V ST - 3D Non-rigid Registration Using Surface and Local Salient Features for Transrectal Ultrasound Image-guided Prostate Biopsy T2 - Proc SPIE Int Soc Opt Eng TI - 3D Non-rigid Registration Using Surface and Local Salient Features for Transrectal Ultrasound Image-guided Prostate Biopsy UR - https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3766999/pdf/nihms362780.pdf VL - 7964 ID - 62 ER - TY - JOUR AB - A fully automatic, multiscale and multiblock fuzzy C-means (MsbFCM) classification method with intensity correction for MR images is presented in this paper. We use a bilateral filter to process MR images and to build a multiscale image series by increasing the standard deviation of spatial function and reducing the standard deviation of range function. We separate every scale image into multiple blocks and for every block a multiscale fuzzy C-means classification method is applied along the scales from the coarse to fine levels to overcome the effect of intensity inhomogeneity. The method is robust for noise MR images with intensity inhomogeneity because of its multiscale and multiblock bilateral filtering scheme. Our method was compared with the conventional FCM, a modified FCM (MFCM) and multiscale FCM (MsFCM) method on synthesized images, simulated brain MR images, and real MR images. The MsbFCM method achieved an overlap ratio of greater than 91% as validated by the ground truth even if original images have 9% noise and 40% intensity inhomogeneity. Experimental results using real MR images demonstrate the effectiveness of the proposed method. Our MsbFCM classification method is accurate and robust for various MR images. AD - Department of Radiology, Emory University, Atlanta, GA 30329. AN - 23358117 AU - Yang, X. AU - Fei, B. C2 - 3552386 DP - Nlm ET - 2011/01/01 LA - eng N1 - Yang, Xiaofeng Fei, Baowei R01 CA156775-02/CA/NCI NIH HHS/United States R01 CA156775-01/CA/NCI NIH HHS/United States R01 CA156775-03/CA/NCI NIH HHS/United States R01 CA156775/CA/NCI NIH HHS/United States UL1 RR025008/RR/NCRR NIH HHS/United States P50 CA128301/CA/NCI NIH HHS/United States United States International Conference on Bioinformatics and Biomedical Engineering : [proceedings]. International Conference on Bioinformatics and Biomedical Engineering Nihms432047 Int Conf Bioinform Biomed Eng. 2011:1-4. PY - 2011 SN - 2151-7614 (Print) 2151-7614 (Linking) SP - 1-4 ST - A MR Brain Classification Method Based on Multiscale and Multiblock Fuzzy C-means T2 - Int Conf Bioinform Biomed Eng TI - A MR Brain Classification Method Based on Multiscale and Multiblock Fuzzy C-means ID - 65 ER - TY - JOUR AB - We are developing a molecular image-directed, 3D ultrasound-guided, targeted biopsy system for improved detection of prostate cancer. In this paper, we propose an automatic 3D segmentation method for transrectal ultrasound (TRUS) images, which is based on multi-atlas registration and statistical texture prior. The atlas database includes registered TRUS images from previous patients and their segmented prostate surfaces. Three orthogonal Gabor filter banks are used to extract texture features from each image in the database. Patient-specific Gabor features from the atlas database are used to train kernel support vector machines (KSVMs) and then to segment the prostate image from a new patient. The segmentation method was tested in TRUS data from 5 patients. The average surface distance between our method and manual segmentation is 1.61 +/- 0.35 mm, indicating that the atlas-based automatic segmentation method works well and could be used for 3D ultrasound-guided prostate biopsy. AD - Department of Radiology, Emory University, Atlanta, GA, USA. AN - 22708024 AU - Yang, X. AU - Schuster, D. AU - Master, V. AU - Nieh, P. AU - Fenster, A. AU - Fei, B. C2 - 3375607 DO - 10.1117/12.877888 [doi] DP - Nlm ET - 2011/01/01 LA - eng N1 - Yang, Xiaofeng Schuster, David Master, Viraj Nieh, Peter Fenster, Aaron Fei, Baowei R01 CA156775-02/CA/NCI NIH HHS/United States R01 CA156775-01/CA/NCI NIH HHS/United States R01 CA156775-03/CA/NCI NIH HHS/United States R01 CA156775/CA/NCI NIH HHS/United States UL1 RR025008/RR/NCRR NIH HHS/United States P50 CA128301/CA/NCI NIH HHS/United States United States Proceedings of SPIE--the International Society for Optical Engineering Nihms362792 Proc SPIE Int Soc Opt Eng. 2011;7964. pii: 796432. Epub 2011 Mar 1. PY - 2011 SN - 0277-786X (Print) 0277-786X (Linking) ST - Automatic 3D Segmentation of Ultrasound Images Using Atlas Registration and Statistical Texture Prior T2 - Proc SPIE Int Soc Opt Eng TI - Automatic 3D Segmentation of Ultrasound Images Using Atlas Registration and Statistical Texture Prior UR - https://www.spiedigitallibrary.org/conference-proceedings-of-spie/7964/1/Automatic-3D-segmentation-of-ultrasound-images-using-atlas-registration-and/10.1117/12.877888.short VL - 7964 ID - 66 ER - TY - JOUR AB - Breast tissue classification can provide quantitative measurements of breast composition, density and tissue distribution for diagnosis and identification of high-risk patients. In this study, we present an automatic classification method to classify high-resolution dedicated breast CT images. The breast is classified into skin, fat and glandular tissue. First, we use a multiscale bilateral filter to reduce noise and at the same time keep edges on the images. As skin and glandular tissue have similar CT values in breast CT images, we use morphologic operations to get the mask of the skin based on information of its position. Second, we use a modified fuzzy C-mean classification method twice, one for the skin and the other for the fatty and glandular tissue. We compared our classified results with manually segmentation results and used Dice overlap ratios to evaluate our classification method. We also tested our method using added noise in the images. The overlap ratios for glandular tissue were above 94. 7% for data from five patients. Evaluation results showed that our method is robust and accurate. AD - Department of Radiology, Emory University. AN - 24027608 AU - Yang, X. AU - Sechopoulos, I. AU - Fei, B. C2 - 3766982 DA - Mar 14 DO - 10.1117/12.877881 [doi] DP - Nlm ET - 2011/03/14 L1 - internal-pdf://2836566121/Yang-2011-Automatic Tissue Classification for.pdf LA - eng N1 - Yang, Xiaofeng Sechopoulos, Ioannis Fei, Baowei R01 CA156775-02/CA/NCI NIH HHS/United States R01 CA156775-01/CA/NCI NIH HHS/United States R01 CA156775-03/CA/NCI NIH HHS/United States R01 CA156775/CA/NCI NIH HHS/United States UL1 RR025008/RR/NCRR NIH HHS/United States P50 CA128301/CA/NCI NIH HHS/United States United States Proceedings of SPIE--the International Society for Optical Engineering Nihms362783 Proc SPIE Int Soc Opt Eng. 2011 Mar 14;7962:79623H. PY - 2011 SN - 0277-786X (Print) 0277-786X (Linking) SP - 79623H ST - Automatic Tissue Classification for High-resolution Breast CT Images Based on Bilateral Filtering T2 - Proc SPIE Int Soc Opt Eng TI - Automatic Tissue Classification for High-resolution Breast CT Images Based on Bilateral Filtering UR - https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3766982/pdf/nihms362783.pdf VL - 7962 ID - 61 ER - TY - CONF A2 - Haynor, David R. A2 - Ourselin, Sebastien AB - Numerical estimation of the size of the kidney is useful in evaluating conditions of the kidney, especially, when serial MR imaging is performed to evaluate the kidney function. This paper presents a new method for automatic segmentation of the kidney in three-dimensional (3D) MR images, by extracting texture features and statistical matching of geometrical shape of the kidney. A set of Wavelet-based support vector machines (W-SVMs) is trained on the MR images. The W-SVMs capture texture priors of MRI for classification of the kidney and non-kidney tissues in different zones around the kidney boundary. In the segmentation procedure, these W-SVMs are trained to tentatively label each voxel around the kidney model as a kidney or non-kidney voxel by texture matching. A probability kidney model is created using 10 segmented MRI data. The model is initially localized based on the intensity profiles in three directions. The weight functions are defined for each labeled voxel for each Wavelet-based, intensity-based, and model-based label. Consequently, each voxel has three labels and three weights for the Wavelet feature, intensity, and probability model. Using a 3D edge detection method, the model is re-localized and the segmented kidney is modified based on a region growing method in the model region. The probability model is re-localized based on the results and this loop continues until the segmentation converges. Experimental results with mouse MRI data show the good performance of the proposed method in segmenting the kidney in MR images. AU - Akbari, Hamed AU - Fei, Baowei CY - San Diego, California DA - 02/2012 DO - 10.1117/12.912028 PB - SPIE PY - 2012 ST - Automatic 3D segmentation of the kidney in MR images using wavelet feature extraction and probability shape model T2 - Proceedings Volume 8314, Medical Imaging 2012: Image Processing TI - Automatic 3D segmentation of the kidney in MR images using wavelet feature extraction and probability shape model VL - 8314 ID - 337 ER - TY - JOUR AB - The proposed macroscopic optical histopathology includes a broad-band light source which is selected to illuminate the tissue glass slide of suspicious pathology, and a hyperspectral camera that captures all wavelength bands from 450 to 950 nm. The system has been trained to classify each histologic slide based on predetermined pathology with light having a wavelength within a predetermined range of wavelengths. This technology is able to capture both the spatial and spectral data of tissue. Highly metastatic human head and neck cancer cells were transplanted to nude mice. After 2-3 weeks, the mice were euthanized and the lymph nodes and lung tissues were sent to pathology. The metastatic cancer is studied in lymph nodes and lungs. The pathological slides were imaged using the hyperspectral camera. The results of the proposed method were compared to the pathologic report. Using hyperspectral images, a library of spectral signatures for different tissues was created. The high-dimensional data were classified using a support vector machine (SVM). The spectra are extracted in cancerous and non-cancerous tissues in lymph nodes and lung tissues. The spectral dimension is used as the input of SVM. Twelve glasses are employed for training and evaluation. The leave-one-out cross-validation method is used in the study. After training, the proposed SVM method can detect the metastatic cancer in lung histologic slides with the specificity of 97.7% and the sensitivity of 92.6%, and in lymph node slides with the specificity of 98.3% and the sensitivity of 96.2%. This method may be able to help pathologists to evaluate many histologic slides in a short time. AD - Department of Radiology and Imaging Sciences, Emory University and Georgia Institute of Technology, Atlanta, GA. AN - 23336061 AU - Akbari, H. AU - Halig, L. V. AU - Zhang, H. AU - Wang, D. AU - Chen, Z. G. AU - Fei, B. C2 - 3546351 DO - 10.1117/12.912026 [doi] DP - Nlm ET - 2013/01/22 L1 - internal-pdf://1042028793/Akbari-2012-Detection of Cancer Metastasis Usi.pdf LA - eng N1 - Akbari, Hamed Halig, Luma V Zhang, Hongzheng Wang, Dongsheng Chen, Zhuo Georgia Fei, Baowei P50 CA128301/CA/NCI NIH HHS/United States P50 CA128613/CA/NCI NIH HHS/United States R01 CA156775/CA/NCI NIH HHS/United States UL1 RR025008/RR/NCRR NIH HHS/United States United States Proceedings of SPIE--the International Society for Optical Engineering Nihms432042 Proc SPIE Int Soc Opt Eng. 2012;8317:831711. Epub 2012 Mar 23. PY - 2012 SN - 0277-786X (Print) 0277-786X (Linking) SP - 831711 ST - Detection of Cancer Metastasis Using a Novel Macroscopic Hyperspectral Method T2 - Proc SPIE Int Soc Opt Eng TI - Detection of Cancer Metastasis Using a Novel Macroscopic Hyperspectral Method UR - https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3546351/pdf/nihms432042.pdf VL - 8317 ID - 48 ER - TY - CONF AU - Fei, Baowei AU - Akbari, Hamed AU - Halig, Luma V PB - IEEE PY - 2012 SN - 1467311839 SP - 62-64 ST - Hyperspectral imaging and spectral-spatial classification for cancer detection T2 - Biomedical Engineering and Informatics (BMEI), 2012 5th International Conference on TI - Hyperspectral imaging and spectral-spatial classification for cancer detection ID - 190 ER - TY - JOUR AN - WOS:000308905805331 AU - Fei, B. AU - Schuster, D. AU - Master, V. AU - Nieh, P. DA - Jun IS - 6 N1 - Times Cited: 4 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) Fei, Baowei /E-6898-2014 Fei, Baowei /0000-0002-9123-9484 0 4 PY - 2012 SN - 0094-2405 SP - 3888-3888 ST - Incorporating PET/CT Images Into 3D Ultrasound-Guided Biopsy of the Prostate T2 - Medical Physics TI - Incorporating PET/CT Images Into 3D Ultrasound-Guided Biopsy of the Prostate UR - ://WOS:000308905805331 VL - 39 ID - 315 ER - TY - JOUR AB - Systematic transrectal ultrasound (TRUS)-guided biopsy is the standard method for a definitive diagnosis of prostate cancer. However, this biopsy approach uses two-dimensional (2D) ultrasound images to guide biopsy and can miss up to 30% of prostate cancers. We are developing a molecular image-directed, three-dimensional (3D) ultrasound image-guided biopsy system for improved detection of prostate cancer. The system consists of a 3D mechanical localization system and software workstation for image segmentation, registration, and biopsy planning. In order to plan biopsy in a 3D prostate, we developed an automatic segmentation method based wavelet transform. In order to incorporate PET/CT images into ultrasound-guided biopsy, we developed image registration methods to fuse TRUS and PET/CT images. The segmentation method was tested in ten patients with a DICE overlap ratio of 92.4% +/- 1.1 %. The registration method has been tested in phantoms. The biopsy system was tested in prostate phantoms and 3D ultrasound images were acquired from two human patients. We are integrating the system for PET/CT directed, 3D ultrasound-guided, targeted biopsy in human patients. AD - Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA 30329. AN - 22708023 AU - Fei, B. AU - Schuster, D. M. AU - Master, V. AU - Akbari, H. AU - Fenster, A. AU - Nieh, P. C2 - 3375601 DO - 10.1117/12.912182 [doi] DP - Nlm ET - 2012/06/19 LA - eng N1 - Fei, Baowei Schuster, David M Master, Viraj Akbari, Hamed Fenster, Aaron Nieh, Peter R01 CA156775-02/CA/NCI NIH HHS/United States R01 CA156775-01/CA/NCI NIH HHS/United States R01 CA156775-03/CA/NCI NIH HHS/United States R01 CA156775/CA/NCI NIH HHS/United States P50 CA128301/CA/NCI NIH HHS/United States P50 CA128613/CA/NCI NIH HHS/United States United States Proceedings of SPIE--the International Society for Optical Engineering Nihms362795 Proc SPIE Int Soc Opt Eng. 2012;2012. pii: 831613. Epub 2012 Feb 16. PY - 2012 SN - 0277-786X (Print) 0277-786X (Linking) ST - A Molecular Image-directed, 3D Ultrasound-guided Biopsy System for the Prostate T2 - Proc SPIE Int Soc Opt Eng TI - A Molecular Image-directed, 3D Ultrasound-guided Biopsy System for the Prostate UR - https://www.spiedigitallibrary.org/conference-proceedings-of-spie/8316/1/A-molecular-image-directed-3D-ultrasound-guided-biopsy-system-for/10.1117/12.912182.short VL - 2012 ID - 55 ER - TY - JOUR AN - WOS:000308905805294 AU - Feng, S. S. J. AU - Bliznakova, K. AU - Qin, X. AU - Fei, B. AU - Sechopoulos, I. DA - Jun IS - 6 N1 - Times Cited: 1 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) Fei, Baowei /E-6898-2014 Fei, Baowei /0000-0002-9123-9484 0 1 PY - 2012 SN - 0094-2405 SP - 3878-3878 ST - Characterization of the Homogeneous Breast Tissue Mixture Approximation for Breast Image Dosimetry T2 - Medical Physics TI - Characterization of the Homogeneous Breast Tissue Mixture Approximation for Breast Image Dosimetry UR - ://WOS:000308905805294 VL - 39 ID - 317 ER - TY - JOUR AN - WOS:000308394400309 AU - MacDonald, Tobey AU - Liu, Jingbo AU - Munson, Jenny AU - Park, Jaekeun AU - Wang, Kenty AU - Fei, Baowei AU - Bellamkonda, Ravi AU - Arbiser, Jack DA - Jun N1 - Times Cited: 0 1 15th International Symposium on Pediatric Neuro-Oncology (ISPNO) JUN 24-27, 2012 Toronto, CANADA Fei, Baowei /E-6898-2014; MacDonald, Tobey/D-4554-2013 Fei, Baowei /0000-0002-9123-9484; 0 PY - 2012 SN - 1522-8517 SP - 83-83 ST - THE APPLICATION OF NANOPARTICLE LIPOSOME-IMPRAMINE BLUE IN THE TREATMENT OF MEDULLOBLASTOMA IN THE SmoA1 TRANSGENIC MICE T2 - Neuro-Oncology TI - THE APPLICATION OF NANOPARTICLE LIPOSOME-IMPRAMINE BLUE IN THE TREATMENT OF MEDULLOBLASTOMA IN THE SmoA1 TRANSGENIC MICE UR - ://WOS:000308394400309 VL - 14 ID - 318 ER - TY - JOUR AU - Taleghani, Pooneh AU - Amzat, Rianot AU - Osunkoya, A AU - Savir-Baruch, Bital AU - Nieh, Peter AU - Master, Viraj AU - Fei, Baowei AU - Fox, Timothy AU - Goodman, Mark AU - Schuster, David IS - supplement 1 PY - 2012 SN - 0161-5505 SP - 1097-1097 ST - Increased expression of Ki-67 correlates with synthetic amino acid PET radiotracer uptake in prostate cancer T2 - Journal of Nuclear Medicine TI - Increased expression of Ki-67 correlates with synthetic amino acid PET radiotracer uptake in prostate cancer VL - 53 ID - 208 ER - TY - JOUR AU - Taleghani, Pooneh AU - Amzat, Rianot AU - Osunkoya, A AU - Savir-Baruch, Bital AU - Nieh, Peter AU - Master, Viraj AU - Fei, Baowei AU - Fox, Timothy AU - Goodman, Mark AU - Schuster, David IS - supplement 1 PY - 2012 SN - 0161-5505 SP - 117-117 ST - Synthetic amino acid PET in primary prostate carcinoma: Correlation of pre-surgical imaging with radical prostatectomy specimens T2 - Journal of Nuclear Medicine TI - Synthetic amino acid PET in primary prostate carcinoma: Correlation of pre-surgical imaging with radical prostatectomy specimens VL - 53 ID - 209 ER - TY - JOUR AB - We developed a three-dimensional (3D) segmentation method for transrectal ultrasound (TRUS) images, which is based on longitudinal image registration and machine learning. Using longitudinal images of each individual patient, we register previously acquired images to the new images of the same subject. Three orthogonal Gabor filter banks were used to extract texture features from each registered image. Patient-specific Gabor features from the registered images are used to train kernel support vector machines (KSVMs) and then to segment the newly acquired prostate image. The segmentation method was tested in TRUS data from five patients. The average surface distance between our and manual segmentation is 1.18 +/- 0.31 mm, indicating that our automatic segmentation method based on longitudinal image registration is feasible for segmenting the prostate in TRUS images. AD - Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA. AN - 24027622 AU - Yang, X. AU - Fei, B. C2 - 3767004 DA - Feb 23 DO - 10.1117/12.912188 [doi] DP - Nlm ET - 2012/02/23 L1 - internal-pdf://0172828148/Yang-2012-3D Prostate Segmentation of Ultrasou.pdf LA - eng N1 - Yang, Xiaofeng Fei, Baowei R01 CA156775-02/CA/NCI NIH HHS/United States R01 CA156775-01/CA/NCI NIH HHS/United States R01 CA156775-03/CA/NCI NIH HHS/United States R01 CA156775/CA/NCI NIH HHS/United States P50 CA128301/CA/NCI NIH HHS/United States United States Proceedings of SPIE--the International Society for Optical Engineering Nihms362793 Proc SPIE Int Soc Opt Eng. 2012 Feb 23;8316:83162O. PY - 2012 SN - 0277-786X (Print) 0277-786X (Linking) SP - 83162O ST - 3D Prostate Segmentation of Ultrasound Images Combining Longitudinal Image Registration and Machine Learning T2 - Proc SPIE Int Soc Opt Eng TI - 3D Prostate Segmentation of Ultrasound Images Combining Longitudinal Image Registration and Machine Learning UR - https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3767004/pdf/nihms362793.pdf VL - 8316 ID - 57 ER - TY - JOUR AB - We have applied image analysis methods in the assessment of human kidney perfusion based on 3D dynamic contrast-enhanced (DCE) MRI data. This approach consists of 3D non-rigid image registration of the kidneys and fuzzy C-mean classification of kidney tissues. The proposed registration method reduced motion artifacts in the dynamic images and improved the analysis of kidney compartments (cortex, medulla, and cavities). The dynamic intensity curves show the successive transition of the contrast agent through kidney compartments. The proposed method for motion correction and kidney compartment classification may be used to improve the validity and usefulness of further model-based pharmacokinetic analysis of kidney function. AD - Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA. AN - 22468206 AU - Yang, X. AU - Ghafourian, P. AU - Sharma, P. AU - Salman, K. AU - Martin, D. AU - Fei, B. C2 - 3314431 DO - 10.1117/12.912190 [doi] DP - Nlm ET - 2012/04/03 L1 - internal-pdf://1173117626/Yang-2012-Nonrigid Registration and Classifica.pdf LA - eng N1 - Yang, Xiaofeng Ghafourian, Pegah Sharma, Puneet Salman, Khalil Martin, Diego Fei, Baowei R01 CA156775-02/CA/NCI NIH HHS/United States R01 CA156775-01/CA/NCI NIH HHS/United States R01 CA156775-03/CA/NCI NIH HHS/United States R01 CA156775/CA/NCI NIH HHS/United States UL1 RR025008/RR/NCRR NIH HHS/United States P50 CA128301/CA/NCI NIH HHS/United States United States Proceedings of SPIE--the International Society for Optical Engineering Nihms362796 Proc SPIE Int Soc Opt Eng. 2012;8314:83140B. Epub 2012 Feb 13. PY - 2012 SN - 0277-786X (Print) 0277-786X (Linking) SP - 83140B ST - Nonrigid Registration and Classification of the Kidneys in 3D Dynamic Contrast Enhanced (DCE) MR Images T2 - Proc SPIE Int Soc Opt Eng TI - Nonrigid Registration and Classification of the Kidneys in 3D Dynamic Contrast Enhanced (DCE) MR Images UR - https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3314431/pdf/nihms362796.pdf VL - 8314 ID - 56 ER - TY - JOUR AB - Numerical estimation of the size of the kidney is useful in evaluating conditions of the kidney, especially, when serial MR imaging is performed to evaluate the kidney function. This paper presents a new method for automatic segmentation of the kidney in three-dimensional (3D) MR images, by extracting texture features and statistical matching of geometrical shape of the kidney. A set of Wavelet-based support vector machines (W-SVMs) is trained on the MR images. The W-SVMs capture texture priors of MRI for classification of the kidney and non-kidney tissues in different zones around the kidney boundary. In the segmentation procedure, these W-SVMs are trained to tentatively label each voxel around the kidney model as a kidney or non-kidney voxel by texture matching. A probability kidney model is created using 10 segmented MRI data. The model is initially localized based on the intensity profiles in three directions. The weight functions are defined for each labeled voxel for each Wavelet-based, intensity-based, and model-based label. Consequently, each voxel has three labels and three weights for the Wavelet feature, intensity, and probability model. Using a 3D edge detection method, the model is re-localized and the segmented kidney is modified based on a region growing method in the model region. The probability model is re-localized based on the results and this loop continues until the segmentation converges. Experimental results with mouse MRI data show the good performance of the proposed method in segmenting the kidney in MR images. AD - Department of Radiology and Imaging Sciences, Emory University and Georgia Institute of Technology, Atlanta, GA. AN - 24027620 AU - Akbari, H. AU - Fei, B. C2 - 3766988 DA - Feb 23 DO - 10.1117/12.912028 [doi] DP - Nlm ET - 2013/09/13 L1 - internal-pdf://2392950519/Akbari-2013-Automatic 3D Segmentation of the K.pdf LA - eng N1 - Akbari, Hamed Fei, Baowei R01 CA156775-02/CA/NCI NIH HHS/United States R01 CA156775-01/CA/NCI NIH HHS/United States R01 CA156775-03/CA/NCI NIH HHS/United States R01 CA156775/CA/NCI NIH HHS/United States UL1 RR025008/RR/NCRR NIH HHS/United States P50 CA128301/CA/NCI NIH HHS/United States United States Proceedings of SPIE--the International Society for Optical Engineering Nihms362797 Proc SPIE Int Soc Opt Eng. 2013 Feb 23;8314:83143D. PY - 2013 SN - 0277-786X (Print) 0277-786X (Linking) SP - 83143D ST - Automatic 3D Segmentation of the Kidney in MR Images Using Wavelet Feature Extraction and Probability Shape Model T2 - Proc SPIE Int Soc Opt Eng TI - Automatic 3D Segmentation of the Kidney in MR Images Using Wavelet Feature Extraction and Probability Shape Model UR - https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3766988/pdf/nihms-362797.pdf VL - 8314 ID - 44 ER - TY - CONF AU - Chen, Xiang AU - Jin, Jie AU - Fei, Baowei PB - Springer, Berlin, Heidelberg PY - 2013 SP - 939-942 ST - Histogram Processing-based Image Enhancement of Digital Radiography for Detection of Cardiac Calcification T2 - World Congress on Medical Physics and Biomedical Engineering May 26-31, 2012, Beijing, China TI - Histogram Processing-based Image Enhancement of Digital Radiography for Detection of Cardiac Calcification ID - 183 ER - TY - JOUR AB - Photodynamictherapy (PDT) uses a drug called a photosensitizer that is excited by irradiation with a laser light of a particular wavelength, which generates reactive singlet oxygen that damages the tumor cells. The photosensitizer and light are inert; therefore, systemic toxicities are minimized in PDT. The synthesis of novel PDT drugs and the use of nanosized carriers for photosensitizers may improve the efficiency of the therapy and the delivery of the drug. In this study, we formulated two nanoparticles with and without a targeting ligand to encapsulate phthalocyanines 4 (Pc 4) molecule and compared their biodistributions. Metastatic human head and neck cancer cells (M4e) were transplanted into nude mice. After 2-3 weeks, the mice were injected with Pc 4, Pc 4 encapsulated into surface coated iron oxide (IO-Pc 4), and IO-Pc 4 conjugated with a fibronectin-mimetic peptide (FMP-IO-Pc 4) which binds specifically to integrin beta1. The mice were imaged using a multispectral camera. Using multispectral images, a library of spectral signatures was created and the signal per pixel of each tumor was calculated, in a grayscale representation of the unmixed signal of each drug. An enhanced biodistribution of nanoparticle encapsulated PDT drugs compared to non-formulated Pc 4 was observed. Furthermore, specific targeted nanoparticles encapsulated Pc 4 has a quicker delivery time and accumulation in tumor tissue than the non-targeted nanoparticles. The nanoparticle-encapsulated PDT drug can have a variety of potential applications in cancer imaging and treatment. AD - Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA. AN - 24236230 AU - Halig, L. V. AU - Wang, D. AU - Wang, A. Y. AU - Chen, Z. G. AU - Fei, B. C2 - 3824266 DA - Mar 29 DO - 10.1117/12.2006492 [doi] DP - Nlm ET - 2013/11/16 LA - eng N1 - Halig, Luma V Wang, Dongsheng Wang, Andrew Y Chen, Zhuo Georgia Fei, Baowei P50 CA128301/CA/NCI NIH HHS/United States R01 CA156775/CA/NCI NIH HHS/United States R21 CA120536/CA/NCI NIH HHS/United States United States Proceedings of SPIE--the International Society for Optical Engineering Nihms514146 Proc SPIE Int Soc Opt Eng. 2013 Mar 29;8672. doi: 10.1117/12.2006492. PY - 2013 SN - 0277-786X (Print) 0277-786X (Linking) ST - Biodistribution Study of Nanoparticle Encapsulated Photodynamic Therapy Drugs Using Multispectral Imaging T2 - Proc SPIE Int Soc Opt Eng TI - Biodistribution Study of Nanoparticle Encapsulated Photodynamic Therapy Drugs Using Multispectral Imaging UR - https://www.spiedigitallibrary.org/conference-proceedings-of-spie/8672/1/Biodistribution-study-of-nanoparticle-encapsulated-photodynamic-therapy-drugs-using-multispectral/10.1117/12.2006492.short VL - 8672 ID - 40 ER - TY - JOUR AB - An automatic framework is proposed to segment right ventricle on ultrasound images. This method can automatically segment both epicardial and endocardial boundaries from a continuous echocardiography series by combining sparse matrix transform (SMT), a training model, and a localized region based level set. First, the sparse matrix transform extracts main motion regions of myocardium as eigenimages by analyzing statistical information of these images. Second, a training model of right ventricle is registered to the extracted eigenimages in order to automatically detect the main location of the right ventricle and the corresponding transform relationship between the training model and the SMT-extracted results in the series. Third, the training model is then adjusted as an adapted initialization for the segmentation of each image in the series. Finally, based on the adapted initializations, a localized region based level set algorithm is applied to segment both epicardial and endocardial boundaries of the right ventricle from the whole series. Experimental results from real subject data validated the performance of the proposed framework in segmenting right ventricle from echocardiography. The mean Dice scores for both epicardial and endocardial boundaries are 89.1%+/-2.3% and 83.6+/-7.3%, respectively. The automatic segmentation method based on sparse matrix transform and level set can provide a useful tool for quantitative cardiac imaging. AD - Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA. AN - 24236228 AU - Qin, X. AU - Cong, Z. AU - Halig, L. V. AU - Fei, B. C2 - 3824270 DA - Mar 13 DO - 10.1117/12.2006490 [doi] DP - Nlm ET - 2013/11/16 LA - eng N1 - Qin, Xulei Cong, Zhibin Halig, Luma V Fei, Baowei P50 CA128301/CA/NCI NIH HHS/United States R01 CA156775/CA/NCI NIH HHS/United States United States Proceedings of SPIE--the International Society for Optical Engineering Nihms514138 Proc SPIE Int Soc Opt Eng. 2013 Mar 13;8669. doi: 10.1117/12.2006490. PY - 2013 SN - 0277-786X (Print) 0277-786X (Linking) ST - Automatic Segmentation of Right Ventricle on Ultrasound Images Using Sparse Matrix Transform and Level Set T2 - Proc SPIE Int Soc Opt Eng TI - Automatic Segmentation of Right Ventricle on Ultrasound Images Using Sparse Matrix Transform and Level Set UR - https://www.spiedigitallibrary.org/conference-proceedings-of-spie/8669/1/Automatic-segmentation-of-right-ventricle-on-ultrasound-images-using-sparse/10.1117/12.2006490.short VL - 8669 ID - 41 ER - TY - JOUR AB - Cardiac myofiber plays an important role in stress mechanism during heart beating periods. The orientation of myofibers decides the effects of the stress distribution and the whole heart deformation. It is important to image and quantitatively extract these orientations for understanding the cardiac physiological and pathological mechanism and for diagnosis of chronic diseases. Ultrasound has been wildly used in cardiac diagnosis because of its ability of performing dynamic and noninvasive imaging and because of its low cost. An extraction method is proposed to automatically detect the cardiac myofiber orientations from high frequency ultrasound images. First, heart walls containing myofibers are imaged by B-mode high frequency (>20 MHz) ultrasound imaging. Second, myofiber orientations are extracted from ultrasound images using the proposed method that combines a nonlinear anisotropic diffusion filter, Canny edge detector, Hough transform, and K-means clustering. This method is validated by the results of ultrasound data from phantoms and pig hearts. AD - Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA. Department of Pediatrics, Emory University School of Medicine, Atlanta, GA. Department of Surgery, Emory University School of Medicine, Atlanta, GA. Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA ; Department of Biomedical Engineering, Emory University and Georgia Institute of Technology ; Department of Mathematics & Computer Science, Emory University, Atlanta, GA. AN - 24392208 AU - Qin, X. AU - Cong, Z. AU - Jiang, R. AU - Shen, M. AU - Wagner, M. B. AU - Kishbom, P. AU - Fei, B. C2 - 3877319 DA - Mar 29 DO - 10.1117/12.2006494 [doi] DP - Nlm ET - 2014/01/07 LA - eng N1 - Qin, Xulei Cong, Zhibin Jiang, Rong Shen, Ming Wagner, Mary B Kishbom, Paul Fei, Baowei P50 CA128301/CA/NCI NIH HHS/United States R01 CA156775/CA/NCI NIH HHS/United States United States Proceedings of SPIE--the International Society for Optical Engineering Nihms514141 Proc SPIE Int Soc Opt Eng. 2013 Mar 29;8675. doi: 10.1117/12.2006494. PY - 2013 SN - 0277-786X (Print) 0277-786X (Linking) ST - Extracting Cardiac Myofiber Orientations from High Frequency Ultrasound Images T2 - Proc SPIE Int Soc Opt Eng TI - Extracting Cardiac Myofiber Orientations from High Frequency Ultrasound Images UR - https://www.spiedigitallibrary.org/conference-proceedings-of-spie/8675/1/Extracting-cardiac-myofiber-orientations-from-high-frequency-ultrasound-images/10.1117/12.2006494.short VL - 8675 ID - 38 ER - TY - CONF AU - Wooten III, Walter J AU - Nye, Jonathan A AU - Schuster, David M AU - Nieh, Peter T AU - Master, Viraj A AU - Votaw, John R AU - Fei, Baowei PB - NIH Public Access PY - 2013 ST - Accuracy evaluation of a 3D ultrasound-guided biopsy system T2 - Proceedings of SPIE TI - Accuracy evaluation of a 3D ultrasound-guided biopsy system VL - 8671 ID - 185 ER - TY - JOUR AB - Purpose:: The objective of this study is to develop hyperspectral imaging technology and advanced image analysis methods for the detection of head and neck cancer. Methods:: A head and neck tumor xenograft model was used in the experiment. The M4E head and neck cancer cells with green fluorescence protein (GFP) were injected into nude mice. Hyperspectral images were acquired from the tumor-bearing mice using a CRI Maestro invivo imaging camera. The wavelength setting was defined within the range of 450–950 nm with 2 nm increments. Two advanced image classification methods were developed to classify normal and cancer tissue on hyperspectral images. In the first method, a tensor-based computation and modeling framework was proposed for the analysis of hyperspectral images for cancer detection. In the second classification method, support vector machines were incorporated into a minimum spanning forest algorithm for differentiating cancer tissue from normal tissue. The classification results were validated by the GPP images of the same animals. Results:: The tensor-based classification method can distinguish between malignant tissue and healthy tissue with an average sensitivity of 97.0% and an average specificity of 91.4% in tumor-bearing mice. The minimum spanning forest algorithm also achieved a high accuracy of more than 97.0% in the animal model. Conclusion:: The hyperspectral imaging and classification technology has been demonstrated in animal models and can have many potential applications in cancer research and management. This research is supported in part by NIH grants (R01CA156775, R21CA176684, and P50CA128301) and Georgia Cancer Coalition Distinguished Clinicians and Scientists Award. AU - Fei, B. AU - Lu, G. AU - Pike, R. AU - Wang, D. AU - Chen, G. DO - 10.1118/1.4889421 IS - 6Part29 KW - Medical imaging Cancer Tissues Biomedical modeling Animals Comparative animal models Image analysis Tissue engineering Fluorescence Experiment design PY - 2014 SN - 2473-4209 SP - 500-501 ST - WE-D-9A-05: Medical Hyperspectral Imaging for the Detection of Head and Neck Cancer in Animal Models T2 - Medical Physics TI - WE-D-9A-05: Medical Hyperspectral Imaging for the Detection of Head and Neck Cancer in Animal Models UR - http://dx.doi.org/10.1118/1.4889421 VL - 41 ID - 336 ER - TY - CPAPER AU - Fei, Baowei AU - Nieh, PT AU - Schuster, D AU - Master, V. CY - Beijing, China DA - June 13-15, 2014 PY - 2014 T2 - The 2nd International Conference of Biomedical Engineering TI - Multimodality molecular imaging for targeted biospy of prostate cancer ID - 349 ER - TY - JOUR AB - Purpose:: Cardiac fibers directly affect the mechanical and electrophysiological properties of the heart. The objective of this study is to explore high-frequency ultrasound imaging for measuring cardiac fiber orientation in an animal model. Methods:: An ex vivo heart model was used in this study. The hearts of male rats were excised, perfused, fixed, and embedded in agar phantoms for two imaging procedures. First, the hearts were first imaged by the Vevo 2100 ultrasound system with a 30 MHz transducer. Second, the hearts were then scanned using a Biospec 7 T MRI system for high-resolution MRI and diffusion tensor imaging (DTI). The geometry of the heart extracted from the MRI is registered with the 3D ultrasound using deformable registration. After registration, deformation fields between both geometries from MRI and ultrasound are obtained. The cardiac fiber orientations imaged by DTI are mapped to ultrasound volumes based on the extracted deformation fields. The registration between 3D ultrasound and MRI of different hearts, e.g. one from the atlas, was further tested. The DTI fiber orientation from the atlas was then mapped to the ultrasound image of a different heart. By this way, we provide a DTI atlas based framework to estimate cardiac fiber orientations from 3D ultrasound images. Results:: After MRI/ultrasound image registration, the Dice similarity scores were more than 90% and the corresponding target errors were less than 0.25 mm. For the atlas-based method, the evaluation results demonstrated the feasibility of determining cardiac fiber orientations from 3D ultrasound. Conclusion:: An atlas-based fiber orientation estimation method was proposed and evaluated for the extraction of cardiac fiber orientation in an animal model. This method and its further improvements in vivo could contribute to understand the cardiac mechanism and help the diagnosis and therapy of heart disease. This research is supported in part by NIH grants (R01CA156775 and R21CA176684), Georgia Research Alliance Distinguished Scientists Award, and the Emory Molecular and Translational Imaging Center (NIH P50CA128301). AU - Fei, B. AU - Qin, X. AU - Wang, S. AU - Shen, M. AU - Wagner, M. AU - Zhang, X. DO - 10.1118/1.4889362 IS - 6Part28 KW - Ultrasonography Heart Magnetic resonance imaging Animals Comparative animal models Ultrasonic transducers Heart disease Mechanical properties Audiometry PY - 2014 SN - 2473-4209 SP - 482-482 ST - TU-F-12A-07: Cardiac Fiber Imaging Using High-Frequency Ultrasound in Animal Models T2 - Medical Physics TI - TU-F-12A-07: Cardiac Fiber Imaging Using High-Frequency Ultrasound in Animal Models UR - http://dx.doi.org/10.1118/1.4889362 VL - 41 ID - 335 ER - TY - CONF AU - Lu, Guolan AU - Halig, Luma AU - Wang, Dongsheng AU - Chen, Zhuo Georgia AU - Fei, Baowei L1 - internal-pdf://1635925713/Lu-2014-Hyperspectral imaging for cancer surgi.pdf PB - NIH Public Access PY - 2014 SP - 90360S ST - Hyperspectral imaging for cancer surgical margin delineation: registration of hyperspectral and histological images T2 - Proceedings of SPIE TI - Hyperspectral imaging for cancer surgical margin delineation: registration of hyperspectral and histological images UR - https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4201054/pdf/nihms613556.pdf VL - 9036 ID - 202 ER - TY - CONF AU - Lu, Guolan AU - Halig, Luma AU - Wang, Dongsheng AU - Chen, Zhuo Georgia AU - Fei, Baowei L1 - internal-pdf://0079515804/Lu-2014-Spectral-spatial classification using.pdf PB - NIH Public Access PY - 2014 SP - 903413 ST - Spectral-spatial classification using tensor modeling for cancer detection with hyperspectral imaging T2 - Proceedings of SPIE TI - Spectral-spatial classification using tensor modeling for cancer detection with hyperspectral imaging UR - https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4201059/pdf/nihms-613551.pdf VL - 9034 ID - 204 ER - TY - CONF AU - Pike, Robert AU - Patton, Samuel K AU - Lu, Guolan AU - Halig, Luma V AU - Wang, Dongsheng AU - Chen, Zhuo Georgia AU - Fei, Baowei L1 - internal-pdf://1577815265/Pike-2014-A minimum spanning forest based hype.pdf PB - NIH Public Access PY - 2014 SP - 90341W ST - A minimum spanning forest based hyperspectral image classification method for cancerous tissue detection T2 - Proceedings of SPIE TI - A minimum spanning forest based hyperspectral image classification method for cancerous tissue detection UR - https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4241346/pdf/nihms613555.pdf VL - 9034 ID - 206 ER - TY - JOUR AB - Digital breast tomosynthesis (DBT) is a pseudo-three-dimensional x-ray imaging modality proposed to decrease the effect of tissue superposition present in mammography, potentially resulting in an increase in clinical performance for the detection and diagnosis of breast cancer. Tissue classification in DBT images can be useful in risk assessment, computer-aided detection and radiation dosimetry, among other aspects. However, classifying breast tissue in DBT is a challenging problem because DBT images include complicated structures, image noise, and out-of-plane artifacts due to limited angular tomographic sampling. In this project, we propose an automatic method to classify fatty and glandular tissue in DBT images. First, the DBT images are pre-processed to enhance the tissue structures and to decrease image noise and artifacts. Second, a global smooth filter based on L0 gradient minimization is applied to eliminate detailed structures and enhance large-scale ones. Third, the similar structure regions are extracted and labeled by fuzzy C-means (FCM) classification. At the same time, the texture features are also calculated. Finally, each region is classified into different tissue types based on both intensity and texture features. The proposed method is validated using five patient DBT images using manual segmentation as the gold standard. The Dice scores and the confusion matrix are utilized to evaluate the classified results. The evaluation results demonstrated the feasibility of the proposed method for classifying breast glandular and fat tissue on DBT images. AD - Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA. Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA. Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA ; Winship Cancer Institute, Emory University, Atlanta, GA. Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA ; Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA ; Department of Mathematics & Computer Science, Emory University, Atlanta, GA ; Winship Cancer Institute, Emory University, Atlanta, GA. AN - 25426271 AU - Qin, X. AU - Lu, G. AU - Sechopoulos, I. AU - Fei, B. C2 - 4241347 DA - Mar 21 DO - 10.1117/12.2043828 [doi] DP - Nlm ET - 2014/11/27 L1 - internal-pdf://3322851385/Qin-2014-Breast Tissue Classification in Digit.pdf LA - eng N1 - Qin, Xulei Lu, Guolan Sechopoulos, Ioannis Fei, Baowei P50 CA128301/CA/NCI NIH HHS/United States R01 CA156775/CA/NCI NIH HHS/United States R01 CA163746/CA/NCI NIH HHS/United States R21 CA176684/CA/NCI NIH HHS/United States United States Proceedings of SPIE--the International Society for Optical Engineering Nihms613554 Proc SPIE Int Soc Opt Eng. 2014 Mar 21;9034:90341V. PY - 2014 SN - 0277-786X (Print) 0277-786X (Linking) SP - 90341V ST - Breast Tissue Classification in Digital Tomosynthesis Images Based on Global Gradient Minimization and Texture Features T2 - Proc SPIE Int Soc Opt Eng TI - Breast Tissue Classification in Digital Tomosynthesis Images Based on Global Gradient Minimization and Texture Features UR - https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4241347/pdf/nihms613554.pdf VL - 9034 ID - 30 ER - TY - JOUR AB - The orientation of cardiac fibers affects the anatomical, mechanical, and electrophysiological properties of the heart. Although echocardiography is the most common imaging modality in clinical cardiac examination, it can only provide the cardiac geometry or motion information without cardiac fiber orientations. If the patient's cardiac fiber orientations can be mapped to his/her echocardiography images in clinical examinations, it may provide quantitative measures for diagnosis, personalized modeling, and image-guided cardiac therapies. Therefore, this project addresses the feasibility of mapping personalized cardiac fiber orientations to three-dimensional (3D) ultrasound image volumes. First, the geometry of the heart extracted from the MRI is translated to 3D ultrasound by rigid and deformable registration. Deformation fields between both geometries from MRI and ultrasound are obtained after registration. Three different deformable registration methods were utilized for the MRI-ultrasound registration. Finally, the cardiac fiber orientations imaged by DTI are mapped to ultrasound volumes based on the extracted deformation fields. Moreover, this study also demonstrated the ability to simulate electricity activations during the cardiac resynchronization therapy (CRT) process. The proposed method has been validated in two rat hearts and three canine hearts. After MRI/ultrasound image registration, the Dice similarity scores were more than 90% and the corresponding target errors were less than 0.25 mm. This proposed approach can provide cardiac fiber orientations to ultrasound images and can have a variety of potential applications in cardiac imaging. AD - Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA. Yerkes National Primate Research Center, Emory University, Atlanta, GA. Department of Pediatrics, Emory University, Atlanta, GA. Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA ; Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA. AN - 25328641 AU - Qin, X. AU - Wang, S. AU - Shen, M. AU - Zhang, X. AU - Wagner, M. B. AU - Fei, B. C2 - 4201058 DA - Mar 12 DO - 10.1117/12.2043821 [doi] DP - Nlm ET - 2014/10/21 L1 - internal-pdf://0499192623/Qin-2014-Mapping Cardiac Fiber Orientations fr.pdf LA - eng N1 - Qin, Xulei Wang, Silun Shen, Ming Zhang, Xiaodong Wagner, Mary B Fei, Baowei P50 CA128301/CA/NCI NIH HHS/United States R01 CA156775/CA/NCI NIH HHS/United States R21 CA176684/CA/NCI NIH HHS/United States United States Proceedings of SPIE--the International Society for Optical Engineering Nihms613557 Proc SPIE Int Soc Opt Eng. 2014 Mar 12;9036:90361O. PY - 2014 SN - 0277-786X (Print) 0277-786X (Linking) SP - 90361O ST - Mapping Cardiac Fiber Orientations from High-Resolution DTI to High-Frequency 3D Ultrasound T2 - Proc SPIE Int Soc Opt Eng TI - Mapping Cardiac Fiber Orientations from High-Resolution DTI to High-Frequency 3D Ultrasound UR - https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4201058/pdf/nihms613557.pdf VL - 9036 ID - 31 ER - TY - GEN AU - Wang, Dongsheng AU - Qin, Xulei AU - Qian, Guoqing AU - Halig, Luma AU - Fei, Baowei AU - Chen, Zhengjia AU - Chen, Zhuo Georgia AU - Saba, Nabil F AU - Shin, Dong M AU - Xu, Hong PB - American Association for Cancer Research PY - 2014 SN - 0008-5472 ST - EGFR targeted iron-oxide nanoparticles for photodynamic therapy in head and neck cancer TI - EGFR targeted iron-oxide nanoparticles for photodynamic therapy in head and neck cancer ID - 215 ER - TY - CPAPER AU - Wang, S. AU - Qin, X AU - Zhang, X. AU - Wagner, MB AU - Fei, BW CY - Milan, Italy DA - May 10-16, 2014 PY - 2014 T2 - Annual Meeting of The Internation Society for Magnetic Resonance in Medicine (ISMRM) 2014 TI - Imaging and visualization of cardiac muscle microstructure in rats using high-resolution MRI ID - 348 ER - TY - JOUR AB - Complete surgical removal of tumor tissue is essential for postoperative prognosis after surgery. Intraoperative tumor imaging and visualization are an important step in aiding surgeons to evaluate and resect tumor tissue in real time, thus enabling more complete resection of diseased tissue and better conservation of healthy tissue. As an emerging modality, hyperspectral imaging (HSI) holds great potential for comprehensive and objective intraoperative cancer assessment. In this paper, we explored the possibility of intraoperative tumor detection and visualization during surgery using HSI in the wavelength range of 450 nm - 900 nm in an animal experiment. We proposed a new algorithm for glare removal and cancer detection on surgical hyperspectral images, and detected the tumor margins in five mice with an average sensitivity and specificity of 94.4% and 98.3%, respectively. The hyperspectral imaging and quantification method have the potential to provide an innovative tool for image-guided surgery. AD - The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA. Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA. Department of Hematology and Medical Oncology, Emory University, Atlanta, GA. The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA ; Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA ; Department of Mathematics & Computer Science, Emory University, Atlanta, GA ; Winship Cancer Institute of Emory University, Atlanta, GA. AN - 26523083 AU - Lu, G. AU - Qin, X. AU - Wang, D. AU - Chen, Z. G. AU - Fei, B. C2 - 4625919 DA - Feb 21 DO - 10.1117/12.2082284 [doi] DP - Nlm ET - 2015/11/03 LA - eng N1 - Lu, Guolan Qin, Xulei Wang, Dongsheng Chen, Zhuo Georgia Fei, Baowei P50 CA128301/CA/NCI NIH HHS/United States R01 CA156775/CA/NCI NIH HHS/United States R21 CA176684/CA/NCI NIH HHS/United States United States Proceedings of SPIE--the International Society for Optical Engineering Nihms716024 Proc SPIE Int Soc Opt Eng. 2015 Feb 21;9415. pii: 94151B. Epub 2015 Mar 18. PY - 2015 SN - 0277-786X (Print) 0277-786X (Linking) ST - Quantitative Wavelength Analysis and Image Classification for Intraoperative Cancer Diagnosis with Hyperspectral Imaging T2 - Proc SPIE Int Soc Opt Eng TI - Quantitative Wavelength Analysis and Image Classification for Intraoperative Cancer Diagnosis with Hyperspectral Imaging UR - https://www.spiedigitallibrary.org/conference-proceedings-of-spie/9415/1/Quantitative-wavelength-analysis-and-image-classification-for-intraoperative-cancer-diagnosis/10.1117/12.2082284.short VL - 9415 ID - 23 ER - TY - CONF AU - Lu, Guolan AU - Qin, Xulei AU - Wang, Dongsheng AU - Chen, Zhuo Georgia AU - Fei, Baowei PB - NIH Public Access PY - 2015 ST - Estimation of tissue optical parameters with hyperspectral imaging and spectral unmixing T2 - Proceedings of SPIE--the International Society for Optical Engineering TI - Estimation of tissue optical parameters with hyperspectral imaging and spectral unmixing VL - 9417 ID - 222 ER - TY - CONF AU - Qin, Xulei AU - Wang, Silun AU - Shen, Ming AU - Zhang, Xiaodong AU - Lerakis, Stamatios AU - Wagner, Mary B AU - Fei, Baowei PB - NIH Public Access PY - 2015 ST - Register cardiac fiber orientations from 3D DTI volume to 2D ultrasound image of rat hearts T2 - Proceedings of SPIE--the International Society for Optical Engineering TI - Register cardiac fiber orientations from 3D DTI volume to 2D ultrasound image of rat hearts VL - 9415 ID - 221 ER - TY - CONF AU - Qin, Xulei AU - Wang, Silun AU - Shen, Ming AU - Zhang, Xiaodong AU - Lerakis, Stamatios AU - Wagner, Mary B AU - Fei, Baowei PB - NIH Public Access PY - 2015 ST - 3D in vivo imaging of rat hearts by high frequency ultrasound and its application in myofiber orientation wrapping T2 - Proceedings of SPIE--the International Society for Optical Engineering TI - 3D in vivo imaging of rat hearts by high frequency ultrasound and its application in myofiber orientation wrapping VL - 9419 ID - 224 ER - TY - JOUR AU - Tade, Funmilayo AU - Odewole, Oluwaseun AU - Halkar, Raghuveer AU - Mittal, Pardeep AU - Nieh, Peter AU - Rossi, Peter AU - Fei, Baowei AU - Savir-Baruch, Bital AU - Goodman, Mark AU - Schuster, David IS - supplement 3 PY - 2015 SN - 0161-5505 SP - 456-456 ST - Anti-[18F] FACBC (FACBC) PET-CT and multiparametric MR (mp-MR) imaging in the detection of recurrent prostate cancer T2 - Journal of Nuclear Medicine TI - Anti-[18F] FACBC (FACBC) PET-CT and multiparametric MR (mp-MR) imaging in the detection of recurrent prostate cancer VL - 56 ID - 229 ER - TY - JOUR AB - Accurate segmentation of the prostate has many applications in prostate cancer diagnosis and therapy. In this paper, we propose a "Supervoxel" based method for prostate segmentation. The prostate segmentation problem is considered as assigning a label to each supervoxel. An energy function with data and smoothness terms is used to model the labeling process. The data term estimates the likelihood of a supervoxel belongs to the prostate according to a shape feature. The geometric relationship between two neighboring supervoxels is used to construct a smoothness term. A three-dimensional (3D) graph cut method is used to minimize the energy function in order to segment the prostate. A 3D level set is then used to get a smooth surface based on the output of the graph cut. The performance of the proposed segmentation algorithm was evaluated with respect to the manual segmentation ground truth. The experimental results on 12 prostate volumes showed that the proposed algorithm yields a mean Dice similarity coefficient of 86.9%+/-3.2%. The segmentation method can be used not only for the prostate but also for other organs. AD - Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA. Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA; Department of Biomedical Engineering, Emory University and Georgia Institute of Technology. AN - 26848206 AU - Tian, Z. AU - Liu, L. AU - Fei, B. C2 - 4736748 DA - Mar 20 DO - 10.1117/12.2082255 [doi] DP - Nlm ET - 2016/02/06 LA - eng N1 - Tian, Zhiqiang Liu, LiZhi Fei, Baowei P50 CA128301/CA/NCI NIH HHS/United States R01 CA156775/CA/NCI NIH HHS/United States R21 CA176684/CA/NCI NIH HHS/United States United States Proceedings of SPIE--the International Society for Optical Engineering Nihms716021 Proc SPIE Int Soc Opt Eng. 2015 Mar 20;9413. pii: 941318. PY - 2015 SN - 0277-786X (Print) 0277-786X (Linking) ST - A supervoxel-based segmentation method for prostate MR images T2 - Proc SPIE Int Soc Opt Eng TI - A supervoxel-based segmentation method for prostate MR images UR - https://www.spiedigitallibrary.org/conference-proceedings-of-spie/9413/1/A-supervoxel-based-segmentation-method-for-prostate-MR-images/10.1117/12.2082255.short VL - 9413 ID - 19 ER - TY - JOUR AB - Most of multi-atlas segmentation methods focus on the registration between the full-size volumes of the data set. Although the transformations obtained from these registrations may be accurate for the global field of view of the images, they may not be accurate for the local prostate region. This is because different magnetic resonance (MR) images have different fields of view and may have large anatomical variability around the prostate. To overcome this limitation, we proposed a two-stage prostate segmentation method based on a fully automatic multi-atlas framework, which includes the detection stage i.e. locating the prostate, and the segmentation stage i.e. extracting the prostate. The purpose of the first stage is to find a cuboid that contains the whole prostate as small cubage as possible. In this paper, the cuboid including the prostate is detected by registering atlas edge volumes to the target volume while an edge detection algorithm is applied to every slice in the volumes. At the second stage, the proposed method focuses on the registration in the region of the prostate vicinity, which can improve the accuracy of the prostate segmentation. We evaluated the proposed method on 12 patient MR volumes by performing a leave-one-out study. Dice similarity coefficient (DSC) and Hausdorff distance (HD) are used to quantify the difference between our method and the manual ground truth. The proposed method yielded a DSC of 83.4%+/-4.3%, and a HD of 9.3 mm+/-2.6 mm. The fully automated segmentation method can provide a useful tool in many prostate imaging applications. AD - Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA. Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA; Department of Biomedical Engineering, Emory University and Georgia Institute of Technology. AN - 26798187 AU - Tian, Z. AU - Liu, L. AU - Fei, B. C2 - 4717836 DA - Mar 20 DO - 10.1117/12.2082229 [doi] DP - Nlm ET - 2016/01/23 LA - eng N1 - Tian, Zhiqiang Liu, LiZhi Fei, Baowei P50 CA128301/CA/NCI NIH HHS/United States R01 CA156775/CA/NCI NIH HHS/United States R21 CA176684/CA/NCI NIH HHS/United States United States Proceedings of SPIE--the International Society for Optical Engineering Nihms716023 Proc SPIE Int Soc Opt Eng. 2015 Mar 20;9413. pii: 941340. PY - 2015 SN - 0277-786X (Print) 0277-786X (Linking) ST - A fully automatic multi-atlas based segmentation method for prostate MR images T2 - Proc SPIE Int Soc Opt Eng TI - A fully automatic multi-atlas based segmentation method for prostate MR images UR - https://www.spiedigitallibrary.org/conference-proceedings-of-spie/9413/1/A-fully-automatic-multi-atlas-based-segmentation-method-for-prostate/10.1117/12.2082229.short VL - 9413 ID - 20 ER - TY - CONF AU - Chung, Hyunkoo AU - Lu, Guolan AU - Tian, Zhiqiang AU - Wang, Dongsheng AU - Chen, Zhuo Georgia AU - Fei, Baowei PB - NIH Public Access PY - 2016 ST - Superpixel-based spectral classification for the detection of head and neck cancer with hyperspectral imaging T2 - Proceedings of SPIE--the International Society for Optical Engineering TI - Superpixel-based spectral classification for the detection of head and neck cancer with hyperspectral imaging VL - 9788 ID - 238 ER - TY - JOUR AB - Accurate extraction of cardiac fiber orientation from diffusion tensor imaging is important for determining heart structure and function. However, the acquisition of magnetic resonance (MR) diffusion tensor images is costly and time consuming. By comparison, cardiac ultrasound imaging is rapid and relatively inexpensive, but it lacks the capability to directly measure fiber orientations. In order to create a detailed heart model from ultrasound data, a three-dimensional (3D) diffusion tensor imaging (DTI) with known fiber orientations can be registered to an ultrasound volume through a geometric mask. After registration, the cardiac orientations from the template DTI can be mapped to the heart using a deformable transformation field. This process depends heavily on accurate fiber orientation extraction from the DTI. In this study, we use the FMRIB Software Library (FSL) to determine cardiac fiber orientations in diffusion weighted images. For the registration between ultrasound and MRI volumes, we achieved an average Dice similarity coefficient (DSC) of 81.6+/-2.1%. For the estimation of fiber orientations from the proposed method, we achieved an acute angle error (AAE) of 22.7+/-3.1 degrees as compared to the direct measurements from DTI. This work provides a new approach to generate cardiac fiber orientation that may be used for many cardiac applications. AD - Department of Nuclear and Radiological Engineering, George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA. Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA. Department of Pediatrics, Emory University, Atlanta, GA. Yerkes National Primate Research Center, Emory University, Atlanta, GA. Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA; Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA. AN - 27660384 AU - Dormer, J. AU - Qin, X. AU - Shen, M. AU - Wang, S. AU - Zhang, X. AU - Jiang, R. AU - Wagner, M. B. AU - Fei, B. C2 - 5029420 DA - Feb 27 DO - 10.1117/12.2217296 [doi] DP - Nlm ET - 2016/09/24 LA - eng N1 - Dormer, James Qin, Xulei Shen, Ming Wang, Silun Zhang, Xiaodong Jiang, Rong Wagner, Mary B Fei, Baowei R01 CA156775/CA/NCI NIH HHS/United States R21 CA120536/CA/NCI NIH HHS/United States R21 CA176684/CA/NCI NIH HHS/United States United States Proceedings of SPIE--the International Society for Optical Engineering Nihms816058 Proc SPIE Int Soc Opt Eng. 2016 Feb 27;9790. pii: 979015. Epub 2016 Apr 1. PY - 2016 SN - 0277-786X (Print) 0277-786X (Linking) ST - Determining Cardiac Fiber Orientation Using FSL and Registered Ultrasound/DTI volumes T2 - Proc SPIE Int Soc Opt Eng TI - Determining Cardiac Fiber Orientation Using FSL and Registered Ultrasound/DTI volumes UR - https://www.spiedigitallibrary.org/conference-proceedings-of-spie/9790/1/Determining-cardiac-fiber-orientation-using-FSL-and-registered-ultrasound-DTI/10.1117/12.2217296.short VL - 9790 ID - 10 ER - TY - JOUR AB - We developed a chemically-induced oral cancer animal model and a computer aided method for tongue cancer diagnosis. The animal model allows us to monitor the progress of the lesions over time. Tongue tissue dissected from mice was sent for histological processing. Representative areas of hematoxylin and eosin (H&E) stained tissue from tongue sections were captured for classifying tumor and non-tumor tissue. The image set used in this paper consisted of 214 color images (114 tumor and 100 normal tissue samples). A total of 738 color, texture, morphometry and topology features were extracted from the histological images. The combination of image features from epithelium tissue and its constituent nuclei and cytoplasm has been demonstrated to improve the classification results. With ten iteration nested cross validation, the method achieved an average sensitivity of 96.5% and a specificity of 99% for tongue cancer detection. The next step of this research is to apply this approach to human tissue for computer aided diagnosis of tongue cancer. AD - The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA. Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA. Department of Hematology and Medical Oncology, Emory University, Atlanta, GA. Department of Otolaryngology, Emory University School of Medicine, Atlanta, GA. The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA; Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA; Department of Mathematics & Computer Science, Emory University, Atlanta, GA; Winship Cancer Institute of Emory University, Atlanta, GA. AN - 27656036 AU - Lu, G. AU - Qin, X. AU - Wang, D. AU - Muller, S. AU - Zhang, H. AU - Chen, A. AU - Chen, Z. G. AU - Fei, B. C2 - 5028209 DA - Feb 27 DO - 10.1117/12.2217286 [doi] DP - Nlm ET - 2016/09/23 LA - eng N1 - Lu, Guolan Qin, Xulei Wang, Dongsheng Muller, Susan Zhang, Hongzheng Chen, Amy Chen, Zhuo Georgia Fei, Baowei R01 CA156775/CA/NCI NIH HHS/United States R21 CA176684/CA/NCI NIH HHS/United States United States Proceedings of SPIE--the International Society for Optical Engineering Nihms816055 Proc SPIE Int Soc Opt Eng. 2016 Feb 27;9791. pii: 97910L. Epub 2016 Mar 23. PY - 2016 SN - 0277-786X (Print) 0277-786X (Linking) ST - Quantitative Diagnosis of Tongue Cancer from Histological Images in an Animal Model T2 - Proc SPIE Int Soc Opt Eng TI - Quantitative Diagnosis of Tongue Cancer from Histological Images in an Animal Model UR - https://www.spiedigitallibrary.org/conference-proceedings-of-spie/9791/1/Quantitative-diagnosis-of-tongue-cancer-from-histological-images-in-an/10.1117/12.2217286.short VL - 9791 ID - 13 ER - TY - JOUR AB - Hyperspectral imaging (HSI) is an emerging modality for medical applications and holds great potential for noninvasive early detection of cancer. It has been reported that early cancer detection can improve the survival and quality of life of head and neck cancer patients. In this paper, we explored the possibility of differentiating between premalignant lesions and healthy tongue tissue using hyperspectral imaging in a chemical induced oral cancer animal model. We proposed a novel classification algorithm for cancer detection using hyperspectral images. The method detected the dysplastic tissue with an average area under the curve (AUC) of 0.89. The hyperspectral imaging and classification technique may provide a new tool for oral cancer detection. AD - The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA. Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA. Department of Hematology and Medical Oncology, Emory University, Atlanta, GA. Department of Otolaryngology, Emory University School of Medicine, Atlanta, GA. The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA; Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA; Department of Mathematics & Computer Science, Emory University, Atlanta, GA; Winship Cancer Institute of Emory University, Atlanta, GA. AN - 27656034 AU - Lu, G. AU - Qin, X. AU - Wang, D. AU - Muller, S. AU - Zhang, H. AU - Chen, A. AU - Chen, Z. G. AU - Fei, B. C2 - 5028204 DA - Feb 27 DO - 10.1117/12.2216553 [doi] DP - Nlm ET - 2016/09/23 LA - eng N1 - Lu, Guolan Qin, Xulei Wang, Dongsheng Muller, Susan Zhang, Hongzheng Chen, Amy Chen, Zhuo Georgia Fei, Baowei R01 CA156775/CA/NCI NIH HHS/United States R21 CA176684/CA/NCI NIH HHS/United States United States Proceedings of SPIE--the International Society for Optical Engineering Nihms816056 Proc SPIE Int Soc Opt Eng. 2016 Feb 27;9788. pii: 978812. Epub 2016 Mar 29. PY - 2016 SN - 0277-786X (Print) 0277-786X (Linking) ST - Hyperspectral Imaging of Neoplastic Progression in a Mouse Model of Oral Carcinogenesis T2 - Proc SPIE Int Soc Opt Eng TI - Hyperspectral Imaging of Neoplastic Progression in a Mouse Model of Oral Carcinogenesis UR - https://www.spiedigitallibrary.org/conference-proceedings-of-spie/9788/1/Hyperspectral-imaging-of-neoplastic-progression-in-a-mouse-model-of/10.1117/12.2216553.short VL - 9788 ID - 15 ER - TY - CONF AU - Ma, Ling AU - Guo, Rongrong AU - Tian, Zhiqiang AU - Venkataraman, Rajesh AU - Sarkar, Saradwata AU - Liu, Xiabi AU - Nieh, Peter T AU - Master, Viraj V AU - Schuster, David M AU - Fei, Baowei PB - NIH Public Access PY - 2016 ST - Random walk based segmentation for the prostate on 3D transrectal ultrasound images T2 - Proceedings of SPIE--the International Society for Optical Engineering TI - Random walk based segmentation for the prostate on 3D transrectal ultrasound images VL - 9786 ID - 235 ER - TY - CONF AU - Ma, Ling AU - Guo, Rongrong AU - Tian, Zhiqiang AU - Venkataraman, Rajesh AU - Sarkar, Saradwata AU - Liu, Xiabi AU - Tade, Funmilayo AU - Schuster, David M AU - Fei, Baowei PB - NIH Public Access PY - 2016 ST - Combining population and patient-specific characteristics for prostate segmentation on 3D CT images T2 - Proceedings of SPIE--the International Society for Optical Engineering TI - Combining population and patient-specific characteristics for prostate segmentation on 3D CT images VL - 9784 ID - 236 ER - TY - JOUR AU - Akin-Akintayo, Oladunni AU - Tade, Funmilayo AU - Mittal, Pardeep AU - Moreno, Courtney AU - Nieh, Peter AU - Rossi, Peter AU - Raghuveer, Halkar AU - Fei, Baowei AU - Goodman, Mark AU - Schuster, David IS - 4 PY - 2017 SN - 0022-5347 SP - e222-e223 ST - MP18-08 COMPARISON OF FLUCICLOVINE (18F) PET-CT AND MRI IN DETECTION OF RECURRENT PROSTATE CANCER T2 - The Journal of Urology TI - MP18-08 COMPARISON OF FLUCICLOVINE (18F) PET-CT AND MRI IN DETECTION OF RECURRENT PROSTATE CANCER VL - 197 ID - 253 ER - TY - CONF AU - Dormer, James AU - Jiang, Rong AU - Wagner, Mary B AU - Fei, Baowei PB - International Society for Optics and Photonics PY - 2017 SP - 101361I-101361I-6 ST - A new method to quantify fiber orientation similarity in registered volumes T2 - SPIE Medical Imaging TI - A new method to quantify fiber orientation similarity in registered volumes ID - 250 ER - TY - CONF AU - Dormer, James D AU - Meng, Yuguang AU - Zhang, Xiaodong AU - Jiang, Rong AU - Wagner, Mary B AU - Fei, Baowei PB - International Society for Optics and Photonics PY - 2017 SP - 101391G-101391G-6 ST - Estimating cardiac fiber orientations in pig hearts using registered ultrasound and MR image volumes T2 - SPIE Medical Imaging TI - Estimating cardiac fiber orientations in pig hearts using registered ultrasound and MR image volumes ID - 252 ER - TY - CONF AU - Fei, Baowei AU - Lu, Guolan AU - Wang, Xu AU - Zhang, Hongzheng AU - Little, James V AU - Magliocca, Kelly R AU - Chen, Amy Y PY - 2017 SP - 100540E-1 ST - Tumor margin assessment of surgical tissue specimen of cancer patients using label-free hyperspectral imaging T2 - Proc. of SPIE Vol TI - Tumor margin assessment of surgical tissue specimen of cancer patients using label-free hyperspectral imaging VL - 10054 ID - 246 ER - TY - CONF AU - Ma, Ling AU - Guoa, Rongrong AU - Zhanga, Guoyi AU - Tadea, Funmilayo AU - Schustera, David M AU - Niehc, Peter AU - Masterc, Viraj AU - Fei, Baowei PB - International Society for Optics and Photonics PY - 2017 SP - 101332O-101332O-9 ST - Automatic segmentation of the prostate on CT images using deep learning and multi-atlas fusion T2 - SPIE Medical Imaging TI - Automatic segmentation of the prostate on CT images using deep learning and multi-atlas fusion ID - 247 ER - TY - CONF AU - Ma, Ling AU - Luc, Guolan AU - Wangd, Dongsheng AU - Wangd, Xu AU - Chend, Zhuo Georgia AU - Mullere, Susan AU - Chene, Amy AU - Fei, Baowei PB - International Society for Optics and Photonics PY - 2017 SP - 101372G-101372G-8 ST - Deep Learning based Classification for Head and Neck Cancer Detection with Hyperspectral Imaging in an Animal Model T2 - SPIE Medical Imaging TI - Deep Learning based Classification for Head and Neck Cancer Detection with Hyperspectral Imaging in an Animal Model ID - 251 ER - TY - CONF AU - Ormenisan-Gherasim, Claudia AU - Tade, Funmilayo AU - Akin-Akintayo, Oladunni O AU - Bilir, Birdal AU - Wiles, Walter G AU - Lu, Guolan AU - Fei, Baowei AU - Moreno, Carlos S AU - Goodman, Mark M AU - Schuster, David M PB - NATURE PUBLISHING GROUP 75 VARICK ST, 9TH FLR, NEW YORK, NY 10013-1917 USA PY - 2017 SN - 0023-6837 SP - 247A-247A ST - Does Injection of 2-Aminobicyclo-(2, 2, 1)-Heptane-2-Carboxylic Acid (BCH) Affect Amino Acid Transporter Density in Prostate Cancer Xenografts? 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