TY - PAT AB - NOVELTY - The processing method (100) involves processing BCT image to determine first classification and second classification of tissue constituents represented by the image (150), such that the second classification is based in part on the first classification, and generating one classified image of the breast based on the processing. The first classification is based on intensity information and the second classification is based on position information. USE - Processing method for BCT image to determine tissue constituent of breast to detect and diagnose breast cancer and to identify women of high-risk. ADVANTAGE - The method enables automatic classification of high resolution BCT images into skin, fat and grandular tissue based on intensity and position information. DETAILED DESCRIPTION - INDEPENDENT CLAIMS are also included for:(1) a computer-readable storage medium storing instructions for processing BCT image to determine tissue constituents of breast; and(2) a system for processing BCT image to determine tissue constituents of breast. DESCRIPTION Of DRAWING(S) - The drawing shows the flowchart of the method to generate classified image of breast.Processing method (100)Receiving BCT image (110)Preprocessing BCT image (120)Correcting BCT image (130)Filtering corrected image (140)Processing BCT image to determine first classification and second classification of tissue constituents represented by the image (150)Quantifying classified breast tissue image (160)Outputting classified breast tissue image (170) AN - DIIDW:2012K81073 AU - Fei, B. AU - Yang, X. AU - Sechopoulos, I. N1 - 0 PB - Univ Emory SN - WO2012109643-A2; WO2012109643-A3 ST - Processing method for breast computed tomography (BCT) image to determine tissue constituents of breast involves generating classified image of breast based of image processing that determines tissue constituents classifications TI - Processing method for breast computed tomography (BCT) image to determine tissue constituents of breast involves generating classified image of breast based of image processing that determines tissue constituents classifications UR - ://DIIDW:2012K81073 ID - 219 ER - TY - JOUR AB - In this paper, we put forward a systematic method to analyze, control and evaluate the safety issues of medical robotics. We created a safety model that consists of three axes to analyze safety factors. Software and hardware are the two material axes. The third axis is the policy that controls all phases of design, production, testing and application of the robot system. The policy was defined as hazard identification and safety insurance control (HISIC) that includes seven principles: definitions and requirements, hazard identification, safety insurance control, safety critical limits, monitoring and control, verification and validation, system log and documentation. HISIC was implemented in the development of a robot for urological applications that was known as URObot. The URObot is a universal robot with different modules adaptable for 3D ultrasound image-guided interstitial laser coagulation, radiation seed implantation, laser resection, and electrical resection of the prostate. Safety was always the key issue in the building of the robot. The HISIC strategies were adopted for safety enhancement in mechanical, electrical and software design. The initial test on URObot showed that HISIC had the potential ability to improve the safety of the system. Further safety experiments are being conducted in our laboratory. (C) 2001 Elsevier Science Ltd. All rights reserved. AN - WOS:000170273500008 AU - Fei, B. W. AU - Ng, W. S. AU - Chauhan, S. AU - Kwoh, C. K. DA - Aug DO - 10.1016/s0951-8320(01)00037-0 M1 - 2 N1 - Times Cited: 18 Chauhan, Sunita/A-3814-2011; Fei, Baowei /E-6898-2014 Fei, Baowei /0000-0002-9123-9484 0 21 PY - 2001 SN - 0951-8320 SP - 183-192 ST - The safety issues of medical robotics T2 - Reliability Engineering & System Safety TI - The safety issues of medical robotics UR - ://WOS:000170273500008 VL - 73 ID - 242 ER - TY - JOUR AB - A three-dimensional (3D) mutual information registration method was created and used to register MRI volumes of the pelvis and prostate. It had special features to improve robustness. First, it used a multi-resolution approach and performed registration from low to high resolution. Second, it used two similarity measures, correlation coefficient at lower resolutions and mutual information at full resolution, because of their particular advantages. Third, we created a method to avoid local minima by restarting the registration with randomly perturbed parameters. The criterion for restarting was a correlation coefficient below an empirically determined threshold. Experiments determined the accuracy of registration under conditions found in potential applications in prostate cancer diagnosis, staging, treatment and interventional MRI (iMRI) guided therapies. Images were acquired in the diagnostic (supine) and treatment position (supine with legs raised). Images were also acquired as a function of bladder filling and the time interval between imaging sessions. Overall studies on three patients and three healthy volunteers, when both volumes in a pair were obtained in the diagnostic position under comparable conditions, bony landmarks and prostate 3D centroids were aligned within 1.6 +/- 0.2 mm and 1.4 +/- 0.2 mm, respectively, values only slightly larger than a voxel. Analysis suggests that actual errors are smaller because of the uncertainty in landmark localization and prostate segmentation. Between the diagnostic and treatment positions, bony landmarks continued to register well, but prostate centroids moved towards the posterior 2.8-3.4 mm. Manual cropping to remove voxels in the legs was necessary to register these images. In conclusion, automatic, rigid body registration is probably sufficiently accurate 0 for Man. applications in prostate cancer. For potential iMRI-guided treatments, the small prostate displacement between the diagnostic and treatment positions can probably be avoided by acquiring volumes in similar positions and by reducing bladder and rectal volumes. AN - WOS:000174531200009 AU - Fei, B. W. AU - Wheaton, A. AU - Lee, Z. H. AU - Duerk, J. L. AU - Wilson, D. L. C7 - Pii s0031-9155(02)29686-4 DA - Mar 7 DO - 10.1088/0031-9155/47/5/309 M1 - 5 N1 - Times Cited: 54 Fei, Baowei /E-6898-2014 Fei, Baowei /0000-0002-9123-9484 0 58 PY - 2002 SN - 0031-9155 SP - 823-838 ST - Automatic MR volume registration and its evaluation for the pelvis and prostate T2 - Physics in Medicine and Biology TI - Automatic MR volume registration and its evaluation for the pelvis and prostate UR - ://WOS:000174531200009 VL - 47 ID - 241 ER - TY - JOUR AB - In this study, we registered live-time interventional magnetic resonance imaging (iMRI) slices with a previously obtained high-resolution MRI volume that in turn can be registered with a variety of functional images, e.g., PET, SPECT, for tumor targeting. We created and evaluated a slice-to-volume (SV) registration algorithm with special features for its potential use in iMRI-guided radio-frequency (RF) thermal ablation of prostate cancer. The algorithm features included a multiresolution approach, two similarity measures, and automatic restarting to avoid local minima. Imaging experiments were performed on volunteers using a conventional 1.5-T MR scanner and a clinical 0.2-T C-arm iMRI system under realistic conditions. Both high-resolution MR volumes and actual iMRI image slices were acquired from the same volunteers. Actual and simulated iMRI images were used to test the dependence of SV registration on image noise, receive coil inhomogeneity, and RF needle artifacts. To quantitatively assess registration, we calculated the mean voxel displacement over a volume of interest between SV registration and volume-to-volume registration, which was previously shown to be quite accurate. More than 800 registration experiments were performed. For transverse image slices covering the prostate, the SV registration algorithm was 100% successful with an error of <2 mm, and the average and standard deviation was only 0.4 mm +/- 0.2 mm. Visualizations such as combined sector display and contour overlay showed excellent registration of the prostate and other organs throughout the pelvis. Error was greater when an image slice was obtained at other orientations and positions, mostly because of inconsistent image content such as that from variable rectal And bladder filling. These preliminary experiments indicate that MR SV registration is sufficiently accurate to aid image-guided therapy. AN - WOS:000183078600005 AU - Fei, B. W. AU - Duerk, J. L. AU - Boll, D. T. AU - Lewin, J. S. AU - Wilson, D. L. DA - Apr DO - 10.1109/tmi.2003.809078 M1 - 4 N1 - Times Cited: 54 Lewin, Jonathan/A-4331-2009; Fei, Baowei /E-6898-2014 Fei, Baowei /0000-0002-9123-9484 0 54 PY - 2003 SN - 0278-0062 SP - 515-525 ST - Slice-to-volume registration and its potential application to interventional MRI-guided radio-frequency thermal ablation of prostate cancer T2 - Ieee Transactions on Medical Imaging TI - Slice-to-volume registration and its potential application to interventional MRI-guided radio-frequency thermal ablation of prostate cancer UR - ://WOS:000183078600005 VL - 22 ID - 238 ER - TY - JOUR AB - A three-dimensional warping registration algorithm was created and compared to rigid body registration of magnetic resonance (MR) pelvic volumes including the prostate. The rigid body registration method combines the advantages of mutual information (MI) and correlation coefficient at different resolutions. Warping registration is based upon independent optimization of many interactively placed control points (CP's) using MI and a thin plate spline transformation. More than 100 registration experiments with 17 MR volume pairs determined the quality of registration under conditions simulating potential interventional MRI-guided treatments of prostate cancer. For image pairs that stress rigid body registration (e.g. supine, the diagnostic position, and legs raised, the treatment position), both visual and numerical evaluation methods showed that warping consistently worked better than rigid body. Experiments showed that approximate to 180 strategically placed CP's were sufficiently expressive to capture important features of the deformation. (C) 2002 Elsevier Science Ltd. All rights reserved. AN - WOS:000182470100002 AU - Fei, B. W. AU - Kemper, C. AU - Wilson, D. L. C7 - Pii s0895-6111(02)00093-9 DA - Jul-Aug DO - 10.1016/s0895-6111(02)00093-9 M1 - 4 N1 - Times Cited: 39 Fei, Baowei /E-6898-2014 Fei, Baowei /0000-0002-9123-9484 0 40 PY - 2003 SN - 0895-6111 SP - 267-281 ST - A comparative study of warping and rigid body registration for the prostate and pelvic MR volumes T2 - Computerized Medical Imaging and Graphics TI - A comparative study of warping and rigid body registration for the prostate and pelvic MR volumes UR - ://WOS:000182470100002 VL - 27 ID - 237 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 - 240 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 - 239 ER - TY - JOUR AB - We are investigating interventional MRI (iMRI) guided radiofrequency thermal ablation for the minimally invasive treatment of the prostate cancer. Nuclear medicine can detect and localize tumor in the prostate not reliably seen in MRI. We intend to combine the advantages of functional images such as nuclear medicine SPECT with iMRI-guided treatments. Our concept is to first register the low-resolution SPECT with a high-resolution MRI volume. Then by registering the high-resolution MR image with live-time iMRI acquisitions, we can, in turn, map the functional data and high-resolution anatomic information to live-time iMRI images for improved tumor targeting. For the first step, we used a three-dimensional mutual information registration method. For the latter, we developed a robust slice to volume (SV) registration algorithm with special features. The concept was tested using image data from three patients and three volunteers. The SV registration accuracy was 0.4 mm +/- 0.2 mm as compared to our volume-to-volume registration that was previously shown to be quite accurate for these image pairs. With our image registration and fusion software, simulation experiments show that it is quite feasible to incorporate SPECT and high-resolution MRI into the iMRI-guided minimally invasive treatment procedures. AN - WOS:000220883100029 AU - Fei, B. W. AU - Lee, Z. H. AU - Boll, D. T. AU - Duerk, J. L. AU - Sodee, D. B. AU - Lewin, J. S. AU - Wilson, D. L. DA - Feb DO - 10.1109/tns.2003.823027 M1 - 1 N1 - Times Cited: 23 1 Lewin, Jonathan/A-4331-2009; Fei, Baowei /E-6898-2014 Fei, Baowei /0000-0002-9123-9484 0 23 PY - 2004 SN - 0018-9499 SP - 177-183 ST - Registration and fusion of SPECT, high-resolution MRI, and interventional MRI for thermal ablation of prostate cancer T2 - Ieee Transactions on Nuclear Science TI - Registration and fusion of SPECT, high-resolution MRI, and interventional MRI for thermal ablation of prostate cancer UR - ://WOS:000220883100029 VL - 51 ID - 236 ER - TY - JOUR AB - Rationale and Objectives. Three-dimensional (3D) nonrigid image registration for potential applications in prostate cancer treatment and interventional magnetic resonance (iMRI) imaging-guided therapies were investigated. Materials and Methods. An almost fully automated 3D nonrigid registration algorithm using mutual information and a thin plate spline (TPS) transformation for MR images of the prostate and pelvis were created and evaluated. In the first step, an automatic rigid body registration with special features was used to capture the global transformation. In the second step, local feature points (FPs) were registered using mutual information. An operator entered only five FPs located at the prostate center, left and right hip joints, and left and right distal femurs. The program automatically determined and optimized other FPs at the external pelvic skin surface and along the femurs. More than 600 control points were used to establish a TPS transformation for deformation of the pelvic region and prostate. Ten volume pairs were acquired from three volunteers in the diagnostic (supine) and treatment positions (supine with legs raised). Results. Various visualization techniques showed that warping rectified the significant pelvic misalignment by the rigid-body method. Gray-value measures of registration quality, including mutual information, correlation coefficient, and intensity difference, all improved with warping. The distance between prostate 3D centroids was 0.7 +/- 0.2 mm after warping compared with 4.9 +/- 3.4 mm with rigid-body registration. Conclusion. Semiautomatic nonrigid registration works better than rigid-body registration when patient position is changed greatly between acquisitions. It could be a useful tool for many applications in the management of prostate. AN - WOS:000230867600004 AU - Fei, B. W. AU - Duerk, J. L. AU - Sodee, D. B. AU - Wilson, D. L. DA - Jul DO - 10.1016/j.acra.2005.03.063 M1 - 7 N1 - Times Cited: 28 Fei, Baowei /E-6898-2014 Fei, Baowei /0000-0002-9123-9484 0 29 PY - 2005 SN - 1076-6332 SP - 815-824 ST - Semiautomatic nonrigid registration for the prostate and pelvic MR volumes T2 - Academic Radiology TI - Semiautomatic nonrigid registration for the prostate and pelvic MR volumes UR - ://WOS:000230867600004 VL - 12 ID - 235 ER - TY - JOUR AB - We are investigating imaging techniques to study the tumor response to photodynamic therapy (PDT). Positron emission tomography (PET) can provide physiological and functional information. High-resolution magnetic resonance imaging (MRI) can provide anatomical and morphological changes. Image registration can combine MRI and PET images for improved tumor monitoring. In this study, we acquired high-resolution MRI and microPET F-18-fluorodeoxyglucose (FDG) images from C3H mice with RIF-1 tumors that were treated with Pc 4-based PDT. We developed two registration methods for this application. For registration of the whole mouse body, we used an automatic three-dimensional, normalized mutual information algorithm. For tumor registration, we developed a finite element model (FEM)-based deformable registration scheme. To assess the quality of whole body registration, we performed slice-by-slice review of both image volumes; manually segmented feature organs, such as the left and right kidneys and the bladder, in each slice; and computed the distance between corresponding centroids. Over 40 volume registration experiments were performed with MRI and microPET images. The distance between corresponding centroids of organs was 1.5 +/- 0.4 mm, which is about 2 pixels of microPET images. The mean volume overlap ratios for tumors were 94.7% and 86.3% for the deformable and rigid registration methods, respectively. Registration of high-resolution MRI and microPET. images combines anatomical and functional information of the tumors and provides a useful tool for evaluating photodynamic therapy. (c) 2006 American Association of Physicists in Medicine. AN - WOS:000236263900018 AU - Fei, B. W. AU - Wang, H. S. AU - Muzic, R. F. AU - Flask, C. AU - Wilson, D. L. AU - Duerk, J. L. AU - Feyes, D. K. AU - Oleinick, N. L. DA - Mar DO - 10.1118/1.2163831 M1 - 3 N1 - Times Cited: 27 wang, hesheng/A-6260-2013; Fei, Baowei /E-6898-2014 Fei, Baowei /0000-0002-9123-9484 0 27 PY - 2006 SN - 0094-2405 SP - 753-760 ST - Deformable and rigid registration of MRI and microPET images for photodynamic therapy of cancer in mice T2 - Medical Physics TI - Deformable and rigid registration of MRI and microPET images for photodynamic therapy of cancer in mice UR - ://WOS:000236263900018 VL - 33 ID - 234 ER - TY - JOUR AB - We are investigating three-dimensional (3D) to two-dimensional (2D) registration methods for computed tomography (CT) and dual-energy digital radiography (DEDR). CT is an established tool for the detection of cardiac calcification. DEDR could be a cost-effective alternative screening tool. In order to utilize CT as the "gold standard" to evaluate the capability of DEDR images for the detection and localization of calcium, we developed an automatic, intensity-based 3D-to-2D registration method for 3D CT volumes and 2D DEDR images. To generate digitally reconstructed radiography (DRR) from the CT volumes, we developed several projection algorithms using the fast shear-warp method. In particular, we created a Gaussian-weighted projection for this application. We used normalized mutual information (NMI) as the similarity measurement. Simulated projection images from CT values were fused with the corresponding DEDR images to evaluate the localization of cardiac calcification. The registration method was evaluated by digital phantoms, physical phantoms, and clinical data sets. The results from the digital phantoms show that the success rate is 100% with a translation difference of less than 0.8 mm and a rotation difference of less than 0.2 degrees. For physical phantom images, the registration accuracy is 0.43 +/- 0.24 mm. Color overlay and 3D visualization of clinical images show that the two images registered well. The NMI values between the DRR and DEDR images improved from 0.21 +/- 0.03 before registration to 0.25 +/- 0.03 after registration. Registration errors measured from anatomic markers decreased from 27.6 +/- 13.6 mm before registration to 2.5 +/- 0.5 mm after registration. Our results show that the automatic 3D-to-2D registration is accurate and robust. This technique can provide a useful tool for correlating DEDR with CT images for screening coronary artery calcification. AN - WOS:000251910200038 AU - Chen, Xiang AU - Gilkeson, Robert C. AU - Fei, Baowei DA - Dec DO - 10.1118/1.2805994 M1 - 12 N1 - Times Cited: 10 Fei, Baowei /E-6898-2014 Fei, Baowei /0000-0002-9123-9484 0 10 PY - 2007 SN - 0094-2405 SP - 4934-4943 ST - Automatic 3D-to-2D registration for CT and dual-energy digital radiography for calcification detection T2 - Medical Physics TI - Automatic 3D-to-2D registration for CT and dual-energy digital radiography for calcification detection UR - ://WOS:000251910200038 VL - 34 ID - 231 ER - TY - JOUR AB - Introduction: High-field magnetic resonance imaging (MRI) is an emerging technique that provides a powerful, non-invasive tool for in vivo studies of cancer therapy in animal models. Photodynamic therapy (PDT) is a relatively new treatment modality for prostate cancer, the second leading cause of cancer mortality in American males. The goal of this study was to evaluate the response of human prostate tumor cells growing as xenografts in athymic nude mice to Pc 4-sensitized PDT. Materials and Methods: PC-3, a cell line derived from a human prostate malignant tumor, was injected intradermally on the back flanks of athymic nude mice. Two tumors were initiated on each mouse. One was treated and the other served as the control. A second-generation photosensitizing drug Pc 4 (0.6 mg/kg body weight) was delivered to each animal by tail vein injection 48 hours before laser illumination (672 nm, 100 mW/cm 2, 150 J/CM2). A dedicated high-field (9.4 T) small-animal MR scanner was used for image acquisitions. A multi-slice multi-echo (MSME) technique, permitting noninvasive in vivo assessment of potential therapeutic effects, was used to measure the T2 values and tumor volumes. Animals were scanned immediately before and after PDT and 24 hours after PDT. T2 values were computed and analyzed for the tumor regions. Results: For the treated tumors, the T2 values significantly increased (P < 0.002) 24 hours after PDT (68.2 +/- 8.5 milliseconds), compared to the pre-PDT values (55.8 +/- 6.6 milliseconds). For the control tumors, there was no significant difference (P = 0.53) between the pre-PDT (52.5 +/- 6.1 milliseconds) and 24-hour post-PDT (54.3 +/- 6.4 milliseconds) values. Histologic analysis showed that PDT-treated tumors demonstrated necrosis and inflammation that was not seen in the control. Discussion: Changes in tumor T2 values measured by multi-slice multi-echo MR imaging provide an assay that could be useful for clinical monitoring of photodynamic therapy of prostate tumors. AN - WOS:000250818200005 AU - Fei, Baowei AU - Wang, Hesheng AU - Meyers, Joseph D. AU - Feyes, Denise K. AU - Oleinick, Nancy L. AU - Duerk, Jeffrey L. DA - Oct DO - 10.1002/lsm.20576 M1 - 9 N1 - Times Cited: 19 wang, hesheng/A-6260-2013; Fei, Baowei /E-6898-2014 Fei, Baowei /0000-0002-9123-9484 0 19 PY - 2007 SN - 0196-8092 SP - 723-730 ST - High-field magnetic resonance imaging of the response of human prostate cancer to pc 4-based photodynamic therapy in an animal model T2 - Lasers in Surgery and Medicine TI - High-field magnetic resonance imaging of the response of human prostate cancer to pc 4-based photodynamic therapy in an animal model UR - ://WOS:000250818200005 VL - 39 ID - 232 ER - TY - JOUR AB - The physiologic variability of blood flow to the prostate has not been studied until this time. We report the vasoactive effects of sildenafil and phenylephrine on blood flow of the normal prostate. Sildenafil increases prostate blood flow by approximately 75% and phenylephrine reduces the flow incrementally. Administration of these drugs with dynamic contrast-enhanced magnetic resonance imaging may improve the diagnosis of cancerous tissue because according to the literature, tumor angiogenic vessels lack the vasoactive physiologic response of the normal tissue. AN - WOS:000243685500017 AU - Haaga, J. R. AU - Exner, A. AU - Fei, B. W. AU - Seftel, A. D. DA - Jan-Feb DO - 10.1038/sj.ijir.3901486 M1 - 1 N1 - Times Cited: 4 Fei, Baowei /E-6898-2014 Fei, Baowei /0000-0002-9123-9484 0 4 PY - 2007 SN - 0955-9930 SP - 110-113 ST - Semiquantitative imaging measurement of baseline and vasomodulated normal prostatic blood flow using sildenafil T2 - International Journal of Impotence Research TI - Semiquantitative imaging measurement of baseline and vasomodulated normal prostatic blood flow using sildenafil UR - ://WOS:000243685500017 VL - 19 ID - 233 ER - TY - JOUR AB - Recent technological improvements have led to increasing clinical use of interface pressure mapping for seating pressure evaluation, which often requires repeated assessments. However, clinical conditions cannot be controlled as closely as research settings, thereby creating challenges to statistical analysis of data. A multistage longitudinal analysis and self-registration (LASR) technique is introduced that emphasizes real-time interface pressure image analysis in three dimensions. Suitable for use in clinical settings, LASR is composed of several modem statistical components, including a segmentation method. The robustness of our segmentation method is also shown. Application of LASR to analysis of data from neuromuscular electrical stimulation (NMES) experiments confirms that NMES improves static seating pressure distributions in the sacral-ischial region over time. Dynamic NMES also improves weight-shifting over time. These changes may reduce the risk of pressure ulcer development. AN - WOS:000258012200005 AU - Bogie, Kath AU - Wang, Xiaofeng AU - Fei, Baowei AU - Sun, Jiayang DA - 2008 DO - 10.1682/jrrd.2007.03.0046 M1 - 4 N1 - Times Cited: 18 Fei, Baowei /E-6898-2014 Fei, Baowei /0000-0002-9123-9484 0 19 PY - 2008 SN - 0748-7711 SP - 523-535 ST - New technique for real-time interface pressure analysis: Getting more out of large image data sets T2 - Journal of Rehabilitation Research and Development TI - New technique for real-time interface pressure analysis: Getting more out of large image data sets UR - ://WOS:000258012200005 VL - 45 ID - 230 ER - TY - JOUR AB - A highly efficient drug vector for photodynamic therapy (PDT) drug delivery was developed by synthesizing PEGylated gold nanoparticle conjugates, which act as a water-soluble and biocompatible "cage" that allows delivery of a hydrophobic drug to its site of PDT action. The dynamics of drug release in vitro in a two-phase solution system and in vivo in cancer-bearing mice indicates that the process of drug delivery is highly efficient, and passive targeting prefers the tumor site. With the Au NP-Pc 4 conjugates, the drug delivery time required for PDT has been greatly reduced to less than 2 h, compared to 2 days for the free drug. AN - WOS:000258293800049 AU - Cheng, Yu AU - Samia, Anna C. AU - Meyers, Joseph D. AU - Panagopoulos, Irene AU - Fei, Baowei AU - Burda, Clemens DA - Aug 13 DO - 10.1021/ja801631c M1 - 32 N1 - Times Cited: 262 Burda, Clemens/C-5107-2008; Burda, Clemens/D-1933-2010; Fei, Baowei /E-6898-2014 Burda, Clemens/0000-0002-7342-2840; Fei, Baowei /0000-0002-9123-9484 0 265 PY - 2008 SN - 0002-7863 SP - 10643-10647 ST - Highly efficient drug delivery with gold nanoparticle vectors for in vivo photodynamic therapy of cancer T2 - Journal of the American Chemical Society TI - Highly efficient drug delivery with gold nanoparticle vectors for in vivo photodynamic therapy of cancer UR - ://WOS:000258293800049 VL - 130 ID - 229 ER - TY - JOUR AN - WOS:000265387200049 AU - Ciancibello, L. AU - Gilkeson, R. AU - Fei, B. DA - May M1 - 5 N1 - Times Cited: 0 109th Annual Meeting of the American-Roentgen-Ray-Society APR 27-MAY 01, 2009 Boston, MA Amer Roentgen Ray Soc Fei, Baowei /E-6898-2014 Fei, Baowei /0000-0002-9123-9484 0 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 UR - ://WOS:000265387200049 VL - 192 ID - 227 ER - TY - JOUR AB - A fully automatic. multiscale fuzzy C-means (MsFCM) classification method for MR images is presented in this paper. We use a diffusion filter to process MR images and to construct a multiscale image series. A multiscale fuzzy C-means classification method is applied along the scales from the coarse to fine levels. The objective function of the conventional fuzzy C-means (FCM) method is modified to allow multiscale classification processing where the result from a coarse scale supervises the classification in the next fine scale. The method is robust for noise and low-contrast MR images because of its multiscale diffusion filtering scheme. The new method was compared with the conventional FCM method and a modified FCM (MFCM) method. Validation studies were performed on synthesized images with various contrasts and on the McGill brain MR image database. Our MsFCM method consistently performed better than the conventional FCM and MFCM methods. The MsFCM method achieved an overlap ratio of greater than 90% as validated by the ground truth. Experiments results on real MR images were given to demonstrate the effectiveness of the proposed method. Our multiscale fuzzy C-means classification method is accurate and robust for various MR images. It can provide a quantitative tool for neuroimaging and other applications. (C) 2008 Elsevier B.V. All rights reserved. AN - WOS:000265224200001 AU - Wang, Hesheng AU - Fei, Baowei DA - Apr DO - 10.1016/j.media.2008.06.014 M1 - 2 N1 - Times Cited: 39 wang, hesheng/A-6260-2013; Fei, Baowei /E-6898-2014 Fei, Baowei /0000-0002-9123-9484 1 48 PY - 2009 SN - 1361-8415 SP - 193-202 ST - A modified fuzzy C-means classification method using a multiscale diffusion filtering scheme T2 - Medical Image Analysis TI - A modified fuzzy C-means classification method using a multiscale diffusion filtering scheme UR - ://WOS:000265224200001 VL - 13 ID - 228 ER - TY - JOUR AB - Photodynamic therapy (PDT) is a relatively new therapy that has shown promise for treating various cancers in both preclinical and clinical studies. The present study evaluated the potential use of PET with radiolabeled choline to monitor early tumor response to PDT in animal models. Methods: Two human prostate cancer models (PC-3 and CWR22) were studied in athymic nude mice. A second-generation photosensitizer, phthalocyanine 4 (Pc 4), was delivered to each animal by a tail vein injection 48 h before laser illumination. Small-animal PET images with C-11-choline were acquired before PDT and at 1, 24, and 48 h after PDT. Time-activity curves of C-11-choline uptake were analyzed before and after PDT. The percentage of the injected dose per gram of tissue was quantified for both treated and control tumors at each time point. In addition, Pc 4-PDT was performed in cell cultures. Cell viability and C-11-choline uptake in PDT-treated and control cells were measured. Results: For treated tumors, normalized C-11-choline uptake decreased significantly 24 and 48 h after PDT, compared with the same tumors before PDT (P < 0.001). For the control tumors, normalized C-11-choline uptake increased significantly. For mice with CWR22 tumors, the prostate-specific antigen level decreased 24 and 48 h after PDT. Pc 4-PDT in cell culture showed that the treated tumor cells, compared with the control cells, had less than 50% C-11-choline activity at 5, 30, and 45 min after PDT, whereas the cell viability test showed that the treated cells were viable longer than 7 h after PDT. Conclusion: PET with C-11-choline is sensitive for detecting early changes associated with Pc 4-PDT in mouse models of human prostate cancer. Choline PET has the potential to determine whether a PDT-treated tumor responds to treatment within 48 h after therapy. AN - WOS:000273263800023 AU - Fei, Baowei AU - Wang, Hesheng AU - Wu, Chunying AU - Chiu, Song-mao DA - Jan DO - 10.2967/jnumed.109.067579 M1 - 1 N1 - Times Cited: 16 wang, hesheng/A-6260-2013; Fei, Baowei /E-6898-2014 Fei, Baowei /0000-0002-9123-9484 0 16 PY - 2010 SN - 0161-5505 SP - 130-138 ST - Choline PET for Monitoring Early Tumor Response to Photodynamic Therapy T2 - Journal of Nuclear Medicine TI - Choline PET for Monitoring Early Tumor Response to Photodynamic Therapy UR - ://WOS:000273263800023 VL - 51 ID - 226 ER - TY - JOUR AB - Purpose: To examine diffusion-weighted MRI (DW-MRI) for assessing the early tumor response to photodynamic therapy (PDT). Materials and Methods: Subcutaneous tumor xenografts of human prostate cancer cells (CWR22) were initiated in athymic nude mice. A second-generation photosensitizer. Pc 4, was delivered to each animal by a tail vein injection 48 h before laser illumination. A dedicated high-field (9.4 Tesla) small animal MR scanner was used to acquire diffusion-weighted MR images pre-PDT and 24 h after the treatment. DW-MRI and apparent diffusion coefficients (ADC) were analyzed for 24 treated and 5 control mice with photosensitizer only or laser light only. Tumor size, prostate specific antigen (PSA) level, and tumor histology were obtained at different time points to examine the treatment effect. Results: Treated mice showed significant tumor size shrinkage and decrease of PSA level within 7 days after the treatment. The average ADC of the 24 treated tumors increased 24 h after PDT (P < 0.001) comparing with pre-PDT. The average ADC was 0.511 +/- 0.119 x 10(-3) mm(2)/s pre-PDT and 0.754 +/- 0.181 x 10(-3) mm(2)/s 24 h after the PDT. There is no significant difference in ADC values pre-PDT and 24 h after PDT in the control tumors (P = 0.20). Conclusion: The change of tumor ADC values measured by DW-MRI may provide a noninvasive imaging marker for monitoring tumor response to Pc 4-PDT as early as 24 h. AN - WOS:000280447300022 AU - Wang, Hesheng AU - Fei, Baowei DA - Aug DO - 10.1002/jmri.22247 M1 - 2 N1 - Times Cited: 8 wang, hesheng/A-6260-2013; Fei, Baowei /E-6898-2014 Fei, Baowei /0000-0002-9123-9484 0 8 PY - 2010 SN - 1053-1807 SP - 409-417 ST - Diffusion-Weighted MRI for Monitoring Tumor Response to Photodynamic Therapy T2 - Journal of Magnetic Resonance Imaging TI - Diffusion-Weighted MRI for Monitoring Tumor Response to Photodynamic Therapy UR - ://WOS:000280447300022 VL - 32 ID - 225 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 - 223 ER - TY - JOUR AN - WOS:000287282301094 AU - Schuster, D. AU - Fei, B. AU - Fox, T. AU - Osunkoya, A. O. DA - Feb N1 - Times Cited: 0 1 100th Annual Meeting United States-and-Canadian-Academy-of-Pathology FEB 26-MAR 04, 2011 San Antonio, TX United States Canadian Acad Pathol Schuster, David/D-6156-2011 0 PY - 2011 SN - 0893-3952 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 - Modern Pathology TI - Histopathologic Correlation of Prostatic Adenocarcinoma on Radical Prostatectomy with Pre-Operative Anti-18F Fluorocyclobutyl-Carboxylic Acid Positron Emission Tomography/Computed Tomography UR - ://WOS:000287282301094 VL - 24 ID - 224 ER - TY - JOUR AB - Purpose: Classification of magnetic resonance (MR) images has many clinical and research applications. Because of multiple factors such as noise, intensity inhomogeneity, and partial volume effects, MR image classification can be challenging. Noise in MRI can cause the classified regions to become disconnected. Partial volume effects make the assignment of a single class to one region difficult. Because of intensity inhomogeneity, the intensity of the same tissue can vary with respect to the location of the tissue within the same image. The conventional "hard" classification method restricts each pixel exclusively to one class and often results in crisp results. Fuzzy C-mean (FCM) classification or "soft" segmentation has been extensively applied to MR images, in which pixels are partially classified into multiple classes using varying memberships to the classes. Standard FCM, however, is sensitive to noise and cannot effectively compensate for intensity inhomogeneities. This paper presents a method to obtain accurate MR brain classification using a modified multiscale and multiblock FCM. Methods: An automatic, multiscale and multiblock fuzzy C-means (MsbFCM) classification method with MR intensity correction is presented in this paper. We use a bilateral filter to process MR images and to build a multiscale image series by increasing the standard deviation of spatial function and by reducing the standard deviation of range function. At each scale, we separate the image into multiple blocks and for every block a multiscale fuzzy C-means classification method is applied along the scales from the coarse to fine levels in order to overcome the effect of intensity inhomogeneity. The result from a coarse scale supervises the classification in the next fine scale. The classification method is tested with noisy MR images with intensity inhomogeneity. Results: Our method was compared with the conventional FCM, a modified FCM (MFCM) and multiscale FCM (MsFCM) method. Validation studies were performed on synthesized images with various contrasts, on the simulated brain MR database, and on real MR images. Our MsbFCM method consistently performed better than the conventional FCM, MFCM, and MsFCM methods. The MsbFCM method achieved an overlap ratio of 91% or higher. Experimental results using real MR images demonstrate the effectiveness of the proposed method. Our MsbFCM classification method is accurate and robust for various MR images. Conclusions: As our classification method did not assume a Gaussian distribution of tissue intensity, it could be used on other image data for tissue classification and quantification. The automatic classification method can provide a useful quantification tool in neuroimaging and other applications. (C) 2011 American Association of Physicists in Medicine. [DOI: 10.1118/1.3584199] AN - WOS:000291405200008 AU - Yang, Xiaofeng AU - Fei, Baowei DA - Jun DO - 10.1118/1.3584199 M1 - 6 N1 - Times Cited: 19 Yang, Xiaofeng/G-9479-2012; Fei, Baowei /E-6898-2014 Fei, Baowei /0000-0002-9123-9484 0 19 PY - 2011 SN - 0094-2405 SP - 2879-2891 ST - A multiscale and multiblock fuzzy C-means classification method for brain MR images T2 - Medical Physics TI - A multiscale and multiblock fuzzy C-means classification method for brain MR images UR - ://WOS:000291405200008 VL - 38 ID - 221 ER - TY - JOUR AB - Based on the Radon transform, a wavelet multiscale denoising method is proposed for MR images. The approach explicitly accounts for the Rician nature of MR data. Based on noise statistics we apply the Radon transform to the original MR images and use the Gaussian noise model to process the MR sinogram image. A translation invariant wavelet transform is employed to decompose the MR 'sinogram' into multiscales in order to effectively denoise the images. Based on the nature of Rician noise we estimate noise variance in different scales. For the final denoised sinogram we apply the inverse Radon transform in order to reconstruct the original MR images. Phantom, simulation brain MR images, and human brain MR images were used to validate our method. The experiment results show the superiority of the proposed scheme over the traditional methods. Our method can reduce Rician noise while preserving the key image details and features. The wavelet denoising method can have wide applications in MRI as well as other imaging modalities. AN - WOS:000286311200045 AU - Yang, Xiaofeng AU - Fei, Baowei C7 - 025803 DA - Feb DO - 10.1088/0957-0233/22/2/025803 M1 - 2 N1 - Times Cited: 10 Yang, Xiaofeng/G-9479-2012; Fei, Baowei /E-6898-2014 Fei, Baowei /0000-0002-9123-9484 0 10 PY - 2011 SN - 0957-0233 ST - A wavelet multiscale denoising algorithm for magnetic resonance (MR) images T2 - Measurement Science & Technology TI - A wavelet multiscale denoising algorithm for magnetic resonance (MR) images UR - ://WOS:000286311200045 VL - 22 ID - 222 ER - TY - JOUR AB - Purpose: Transrectal ultrasound (TRUS) imaging is clinically used in prostate biopsy and therapy. Segmentation of the prostate on TRUS images has many applications. In this study, a three-dimensional (3D) segmentation method for TRUS images of the prostate is presented for 3D ultrasound-guided biopsy. Methods: This segmentation method utilizes a statistical shape, texture information, and intensity profiles. A set of wavelet support vector machines (W-SVMs) is applied to the images at various subregions of the prostate. The W-SVMs are trained to adaptively capture the features of the ultrasound images in order to differentiate the prostate and nonprostate tissue. This method consists of a set of wavelet transforms for extraction of prostate texture features and a kernel-based support vector machine to classify the textures. The voxels around the surface of the prostate are labeled in sagittal, coronal, and transverse planes. The weight functions are defined for each labeled voxel on each plane and on the model at each region. In the 3D segmentation procedure, the intensity profiles around the boundary between the tentatively labeled prostate and nonprostate tissue are compared to the prostate model. Consequently, the surfaces are modified based on the model intensity profiles. The segmented prostate is updated and compared to the shape model. These two steps are repeated until they converge. Manual segmentation of the prostate serves as the gold standard and a variety of methods are used to evaluate the performance of the segmentation method. Results: The results from 40 TRUS image volumes of 20 patients show that the Dice overlap ratio is 90.3% +/- 2.3% and that the sensitivity is 87.7% +/- 4.9%. Conclusions: The proposed method provides a useful tool in our 3D ultrasound image-guided prostate biopsy and can also be applied to other applications in the prostate. (C) 2012 American Association of Physicists in Medicine. [http://dx.doi.org/10.1118/1.4709607] AN - WOS:000308905800004 AU - Akbari, Hamed AU - Fei, Baowei DA - Jun DO - 10.1118/1.4709607 M1 - 6 N1 - Times Cited: 12 Fei, Baowei /E-6898-2014 Fei, Baowei /0000-0002-9123-9484 0 12 PY - 2012 SN - 0094-2405 SP - 2972-2984 ST - 3D ultrasound image segmentation using wavelet support vector machines T2 - Medical Physics TI - 3D ultrasound image segmentation using wavelet support vector machines UR - ://WOS:000308905800004 VL - 39 ID - 214 ER - TY - JOUR AB - Hyperspectral imaging (HSI) is an emerging modality for various medical applications. Its spectroscopic data might be able to be used to noninvasively detect cancer. Quantitative analysis is often necessary in order to differentiate healthy from diseased tissue. We propose the use of an advanced image processing and classification method in order to analyze hyperspectral image data for prostate cancer detection. The spectral signatures were extracted and evaluated in both cancerous and normal tissue. Least squares support vector machines were developed and evaluated for classifying hyperspectral data in order to enhance the detection of cancer tissue. This method was used to detect prostate cancer in tumor-bearing mice and on pathology slides. Spatially resolved images were created to highlight the differences of the reflectance properties of cancer versus those of normal tissue. Preliminary results with 11 mice showed that the sensitivity and specificity of the hyperspectral image classification method are 92.8% to 2.0% and 96.9% to 1.3%, respectively. Therefore, this imaging method may be able to help physicians to dissect malignant regions with a safe margin and to evaluate the tumor bed after resection. This pilot study may lead to advances in the optical diagnosis of prostate cancer using HSI technology. (C) 2012 Society of Photo-Optical Instrumentation Engineers (SPIE). [DOI: 10.1117/1.JBO.17.7.076005] AN - WOS:000307989500032 AU - Akbari, Hamed AU - Halig, Luma V. AU - Schuster, David M. AU - Osunkoya, Adeboye AU - Master, Viraj AU - Nieh, Peter T. AU - Chen, Georgia Z. AU - Fei, Baowei C7 - 076005 DA - Jul DO - 10.1117/1.jbo.17.7.076005 M1 - 7 N1 - Times Cited: 17 Fei, Baowei /E-6898-2014 Fei, Baowei /0000-0002-9123-9484 0 18 PY - 2012 SN - 1083-3668 ST - Hyperspectral imaging and quantitative analysis for prostate cancer detection T2 - Journal of Biomedical Optics TI - Hyperspectral imaging and quantitative analysis for prostate cancer detection UR - ://WOS:000307989500032 VL - 17 ID - 213 ER - TY - JOUR AN - WOS:000308905805331 AU - Fei, B. AU - Schuster, D. AU - Master, V. AU - Nieh, P. DA - Jun M1 - 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 - 216 ER - TY - JOUR AB - Purpose: Combined MR/PET is a relatively new, hybrid imaging modality. A human MR/PET prototype system consisting of a Siemens 3T Trio MR and brain PET insert was installed and tested at our institution. Its present design does not offer measured attenuation correction (AC) using traditional transmission imaging. This study is the development of quantification tools including MR-based AC for quantification in combined MR/PET for brain imaging. Methods: The developed quantification tools include image registration, segmentation, classification, and MR-based AC. These components were integrated into a single scheme for processing MR/PET data. The segmentation method is multiscale and based on the Radon transform of brain MR images. It was developed to segment the skull on T1-weighted MR images. A modified fuzzy C-means classification scheme was developed to classify brain tissue into gray matter, white matter, and cerebrospinal fluid. Classified tissue is assigned an attenuation coefficient so that AC factors can be generated. PET emission data are then reconstructed using a three-dimensional ordered sets expectation maximization method with the MR-based AC map. Ten subjects had separate MR and PET scans. The PET with [C-11]PIB was acquired using a high-resolution research tomography (HRRT) PET. MR-based AC was compared with transmission (TX)-based AC on the HRRT. Seventeen volumes of interest were drawn manually on each subject image to compare the PET activities between the MR-based and TX-based AC methods. Results: For skull segmentation, the overlap ratio between our segmented results and the ground truth is 85.2 +/- 2.6%. Attenuation correction results from the ten subjects show that the difference between the MR and TX-based methods was <6.5%. Conclusions: MR-based AC compared favorably with conventional transmission-based AC. Quantitative tools including registration, segmentation, classification, and MR-based AC have been developed for use in combined MR/PET. (C) 2012 American Association of Physicists in Medicine. [http://dx.doi.org/10.1118/1.4754796] AN - WOS:000310101900062 AU - Fei, Baowei AU - Yang, Xiaofeng AU - Nye, Jonathon A. AU - Aarsvold, John N. AU - Raghunath, Nivedita AU - Cervo, Morgan AU - Stark, Rebecca AU - Meltzer, Carolyn C. AU - Votaw, John R. DA - Oct DO - 10.1118/1.4754796 M1 - 10 N1 - Times Cited: 13 Yang, Xiaofeng/G-9479-2012; Fei, Baowei /E-6898-2014 Fei, Baowei /0000-0002-9123-9484 0 13 PY - 2012 SN - 0094-2405 SP - 6443-6454 ST - MR/PET quantification tools: Registration, segmentation, classification, and MR-based attenuation correction T2 - Medical Physics TI - MR/PET quantification tools: Registration, segmentation, classification, and MR-based attenuation correction UR - ://WOS:000310101900062 VL - 39 ID - 211 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 M1 - 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 - 215 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 - 217 ER - TY - JOUR AB - Cardiovascular disease is the leading cause of global mortality, yet its early detection remains a vexing problem of modern medicine. Although the computed tomography (CT) calcium score predicts cardiovascular risk, relatively high cost ($250-400) and radiation dose (13 mSv) limit its universal utility as a screening tool. Dual-energy digital subtraction radiography (DE; <$60, 0.07 mSv) enables detection of calcified structures with high sensitivity. In this pilot study, we examined DE radiography's ability to quantify coronary artery calcification (CAC). We identified 25 patients who underwent non-contrast CT and DE chest imaging performed within 12 months using documented CAC as the major inclusion criteria. A DE calcium score was developed based on pixel intensity multiplied by the area of the calcified plaque. DE scores were plotted against CT scores. Subsequently, a validation cohort of 14 additional patients was independently evaluated to confirm the accuracy and precision of CAC quantification, yielding a total of 39 subjects. Among all subjects (n=39), the DE score demonstrated a correlation coefficient of 0.87 (p<0.0001) when compared with the CT score. For the 13 patients with CT scores of <400, the correlation coefficient was -0.26. For the 26 patients with CT scores of >= 400, the correlation coefficient yielded 0.86. This pilot study demonstrates the feasibility of DE radiography to identify patients at the highest cardiovascular risk. DE radiography's accuracy at lower scores remains unclear. Further evaluation of DE radiography as an inexpensive and low-radiation imaging tool to diagnose cardiovascular disease appears warranted. AN - WOS:000304113400019 AU - Mafi, John N. AU - Fei, Baowei AU - Roble, Sharon AU - Dota, Anthony AU - Katrapati, Prashanth AU - Bezerra, Hiram G. AU - Wang, Hesheng AU - Wang, Wei AU - Ciancibello, Leslie AU - Costa, Marco AU - Simon, Daniel I. AU - Orringer, Carl E. AU - Gilkeson, Robert C. DA - Feb DO - 10.1007/s10278-011-9385-y M1 - 1 N1 - Times Cited: 5 wang, hesheng/A-6260-2013; Fei, Baowei /E-6898-2014; Roble, Sharon/E-3966-2011 Fei, Baowei /0000-0002-9123-9484; 0 5 PY - 2012 SN - 0897-1889 SP - 129-136 ST - Assessment of Coronary Artery Calcium Using Dual-Energy Subtraction Digital Radiography T2 - Journal of Digital Imaging TI - Assessment of Coronary Artery Calcium Using Dual-Energy Subtraction Digital Radiography UR - ://WOS:000304113400019 VL - 25 ID - 218 ER - TY - JOUR AB - Purpose: To compare the estimate of normalized glandular dose in mammography and breast CT imaging obtained using the actual glandular tissue distribution in the breast to that obtained using the homogeneous tissue mixture approximation. Methods: Twenty volumetric images of patient breasts were acquired with a dedicated breast CT prototype system and the voxels in the breast CT images were automatically classified into skin, adipose, and glandular tissue. The breasts in the classified images underwent simulated mechanical compression to mimic the conditions present during mammographic acquisition. The compressed thickness for each breast was set to that achieved during each patient's last screening cranio-caudal (CC) acquisition. The volumetric glandular density of each breast was computed using both the compressed and uncompressed classified images, and additional images were created in which all voxels representing adipose and glandular tissue were replaced by a homogeneous mixture of these two tissues in a proportion corresponding to each breast's volumetric glandular density. All four breast images (compressed and uncompressed; heterogeneous and homogeneous tissue) were input into Monte Carlo simulations to estimate the normalized glandular dose during mammography (compressed breasts) and dedicated breast-CT (uncompressed breasts). For the mammography simulations the x-ray spectra used was that used during each patient's last screening CC acquisition. For the breast CT simulations, two x-ray spectra were used, corresponding to the x-ray spectra with the lowest and highest energies currently being used in dedicated breast CT prototype systems under clinical investigation. The resulting normalized glandular dose for the heterogeneous and homogeneous versions of each breast for each modality was compared. Results: For mammography, the normalized glandular dose based on the homogeneous tissue approximation was, on average, 27% higher than that estimated using the true heterogeneous glandular tissue distribution (Wilcoxon Signed Rank Test p = 0.00046). For dedicated breast CT, the overestimation of normalized glandular dose was, on average, 8% (49 kVp spectrum, p = 0.00045) and 4% (80 kVp spectrum, p = 0.000089). Only two cases in mammography and two cases in dedicated breast CT with a tube voltage of 49 kVp resulted in lower dose estimates for the homogeneous tissue approximation compared to the heterogeneous tissue distribution. Conclusions: The normalized glandular dose based on the homogeneous tissue mixture approximation results in a significant overestimation of dose to the imaged breast. This overestimation impacts the use of dose estimates in absolute terms, such as for risk estimates, and may impact some comparative studies, such as when modalities or techniques with different x-ray energies are used. The error introduced by the homogeneous tissue mixture approximation in higher energy x-ray modalities, such as dedicated breast CT, although statistically significant, may not be of clinical concern. Further work is required to better characterize this overestimation and potentially develop new metrics or correction factors to better estimate the true glandular dose to breasts undergoing imaging with ionizing radiation. 0 2012 American Association of Physicists in Medicine. [http://dx.doi.org/10.1118/1.4737025] AN - WOS:000307917600043 AU - Sechopoulos, Ioannis AU - Bliznakova, Kristina AU - Qin, Xulei AU - Fei, Baowei AU - Feng, Steve Si Jia DA - Aug DO - 10.1118/1.4737025 M1 - 8 N1 - Times Cited: 6 Fei, Baowei /E-6898-2014 Fei, Baowei /0000-0002-9123-9484 0 6 PY - 2012 SN - 0094-2405 SP - 5050-5059 ST - Characterization of the homogeneous tissue mixture approximation in breast imaging dosimetry T2 - Medical Physics TI - Characterization of the homogeneous tissue mixture approximation in breast imaging dosimetry UR - ://WOS:000307917600043 VL - 39 ID - 212 ER - TY - JOUR AB - Purpose: Partial volume effect in positron emission tomography (PET) can cause incorrect quantification of radiopharmaceutical uptake in functional imaging. A PET partial volume correction method is presented to attenuate partial volume blurring and to yield voxel-based corrected PET images. Methods: By modeling partial volume effect as a convolution of point spread function of the PET scanner, the reconstructed PET images are corrected by iterative deconvolution with an edge-preserving smoothness constraint. The constraint is constructed to restore discontinuities extracted from coregistered MR images but maintains the smoothness in radioactivity distribution. The correction is implemented in a Bayesian deconvolution framework and is solved by a conjugate gradient method. The performance of the method was compared with the geometric transfer matrix (GTM) method on a simulated dataset. The method was evaluated on synthesized brain FDG-PET data and phantom MRI-PET experiments. Results: The true PET activity of objects with a size of greater than the full-width at half maximum of the point spread function has been effectively restored in the simulated data. The partial volume correction method is quantitatively comparable to the GTM method. For synthesized FDG-PET with true activity 0 mu ci/cc for cerebrospinal fluid (CSF), 228 mu ci/cc for white matter (WM), and 621 mu ci/cc for gray matter (GM), the method has improved the radioactivity quantification from 186 +/- 16 mu ci/cc to 30 +/- 7 mu ci/cc in CSF, 317 +/- 15 mu ci/cc to 236 +/- 10 mu ci/cc for WM, 438 +/- 4 mu ci/ cc to 592 +/- 5 mu ci/cc for GM. Both visual and quantitative assessments show improvement of partial volume correction in the synthesized and phantom experiments. Conclusions: The partial volume correction method improves the quantification of PET images. The method is comparable to the GTM method but does not need MR image segmentation or prior tracer distribution information. The voxel-based method can be particularly useful for combined PET/MRI studies. (C) 2012 American Association of Physicists in Medicine. [DOI: 10.1118/1.3665704] AN - WOS:000298812200020 AU - Wang, Hesheng AU - Fei, Baowei DA - Jan DO - 10.1118/1.3665704 M1 - 1 N1 - Times Cited: 12 wang, hesheng/A-6260-2013; Fei, Baowei /E-6898-2014 Fei, Baowei /0000-0002-9123-9484 0 12 PY - 2012 SN - 0094-2405 SP - 179-194 ST - An MR image-guided, voxel-based partial volume correction method for PET images T2 - Medical Physics TI - An MR image-guided, voxel-based partial volume correction method for PET images UR - ://WOS:000298812200020 VL - 39 ID - 220 ER - TY - JOUR AB - Purpose: To develop and test an automated algorithm to classify the different tissues present in dedicated breast CT images. Methods: The original CT images are first corrected to overcome cupping artifacts, and then a multiscale bilateral filter is used to reduce noise while keeping edge information on the images. As skin and glandular tissues have similar CT values on breast CT images, morphologic processing is used to identify the skin mask based on its position information. A modified fuzzy C-means (FCM) classification method is then used to classify breast tissue as fat and glandular tissue. By combining the results of the skin mask with the FCM, the breast tissue is classified as skin, fat, and glandular tissue. To evaluate the authors' classification method, the authors use Dice overlap ratios to compare the results of the automated classification to those obtained by manual segmentation on eight patient images. Results: The correction method was able to correct the cupping artifacts and improve the quality of the breast CT images. For glandular tissue, the overlap ratios between the authors' automatic classification and manual segmentation were 91.6% +/- 2.0%. Conclusions: A cupping artifact correction method and an automatic classification method were applied and evaluated for high-resolution dedicated breast CT images. Breast tissue classification can provide quantitative measurements regarding breast composition, density, and tissue distribution. (c) 2012 American Association of Physicists in Medicine. [http://dx.doi.org/10.1118/1.4754654] AN - WOS:000310101900058 AU - Yang, Xiaofeng AU - Wu, Shengyong AU - Sechopoulos, Ioannis AU - Fei, Baowei DA - Oct DO - 10.1118/1.4754654 M1 - 10 N1 - Times Cited: 11 Yang, Xiaofeng/G-9479-2012; Fei, Baowei /E-6898-2014 Fei, Baowei /0000-0002-9123-9484 0 11 PY - 2012 SN - 0094-2405 SP - 6397-6406 ST - Cupping artifact correction and automated classification for high-resolution dedicated breast CT images Xiaofeng Yang and Shengyong Wu T2 - Medical Physics TI - Cupping artifact correction and automated classification for high-resolution dedicated breast CT images Xiaofeng Yang and Shengyong Wu UR - ://WOS:000310101900058 VL - 39 ID - 210 ER - TY - JOUR AB - An automatic segmentation framework is proposed to segment the right ventricle (RV) in echocardiographic images. The method can automatically segment both epicardial and endocardial boundaries from a continuous echocardiography series by combining sparse matrix transform, a training model, and a localized region-based level set. First, the sparse matrix transform extracts main motion regions of the myocardium as eigen-images by analyzing the statistical information of the images. Second, an RV training model is registered to the eigen-images in order to locate the position of the RV. Third, the training model is adjusted and then serves as an optimized initialization for the segmentation of each image. Finally, based on the initializations, a localized, region-based level set algorithm is applied to segment both epicardial and endocardial boundaries in each echocardiograph. Three evaluation methods were used to validate the performance of the segmentation framework. The Dice coefficient measures the overall agreement between the manual and automatic segmentation. The absolute distance and the Hausdorff distance between the boundaries from manual and automatic segmentation were used to measure the accuracy of the segmentation. Ultrasound images of human subjects were used for validation. For the epicardial and endocardial boundaries, the Dice coefficients were 90.8 +/- 1.7% and 87.3 +/- 1.9%, the absolute distances were 2.0 +/- 0.42 mm and 1.79 +/- 0.45 mm, and the Hausdorff distances were 6.86 +/- 1.71 mm and 7.02 +/- 1.17 mm, respectively. The automatic segmentation method based on a sparse matrix transform and level set can provide a useful tool for quantitative cardiac imaging. AN - WOS:000326377100012 AU - Qin, Xulei AU - Cong, Zhibin AU - Fei, Baowei DA - Nov 7 DO - 10.1088/0031-9155/58/21/7609 M1 - 21 N1 - Times Cited: 7 Fei, Baowei /E-6898-2014 Fei, Baowei /0000-0002-9123-9484 0 7 PY - 2013 SN - 0031-9155 SP - 7609-7624 ST - Automatic segmentation of right ventricular ultrasound images using sparse matrix transform and a level set T2 - Physics in Medicine and Biology TI - Automatic segmentation of right ventricular ultrasound images using sparse matrix transform and a level set UR - ://WOS:000326377100012 VL - 58 ID - 204 ER - TY - JOUR AB - Purpose: To analyze the frequency domain characteristics of the signal in mammography images and breast tomosynthesis projections with patient tissue texture due to detected scattered x-rays. Methods: Acquisitions of x-ray projection images of 19 different patient breasts were simulated using previously acquired volumetric patient images. Acquisition of these images was performed with a dedicated breast CT prototype system, and the images were classified into voxels representing skin, adipose, and glandular tissue with a previously validated automated algorithm. The classified three dimensional images then underwent simulated mechanical compression representing that which is performed during acquisition of mammography and breast tomosynthesis images. The acquisition of projection images of each patient breast was simulated using Monte Carlo methods with each simulation resulting in two images: one of the primary (non-scattered) signal and one of the scatter signal. To analyze the scatter signal for both mammography and breast tomosynthesis, two projections images of each patient breast were simulated, one with the x-ray source positioned at 0 degrees (mammography and central tomosynthesis projection) and at 30 degrees (wide tomosynthesis projection). The noise power spectra (NPS) for both the scatter signal alone and the total signal (primary + scatter) for all images were obtained and the combined results of all patients analyzed. The total NPS was fit to the expected power-law relationship NPS(f) = k/f boolean AND beta and the results were compared with those previously published on the power spectrum characteristics of mammographic texture. The scatter signal alone was analyzed qualitatively and a power-law fit was also performed. Results: The mammography and tomosynthesis projections of three patient breasts were too small to analyze, so a total of 16 patient breasts were analyzed. The values of beta for the total signal of the 0 degrees projections agreed well with previously published results. As expected, the scatter power spectrum reflected a fast drop-off with increasing spatial frequency, with a reduction of four orders of magnitude by 0.1 lp/mm. The beta values for the scatter signal were 6.14 and 6.39 for the 0 degrees and 30 degrees projections, respectively. Conclusions: Although the low-frequency characteristics of scatter in mammography and breast tomosynthesis were known, a quantitative analysis of the frequency domain characteristics of this signal was needed in order to optimize previously proposed software-based x-ray scatter reduction algorithms for these imaging modalities. (c) 2013 American Association of Physicists in Medicine. AN - WOS:000325394400021 AU - Sechopoulos, Ioannis AU - Bliznakova, Kristina AU - Fei, Baowei C7 - Unsp 101905 DA - Oct DO - 10.1118/1.4820442 M1 - 10 N1 - Times Cited: 0 Fei, Baowei /E-6898-2014 Fei, Baowei /0000-0002-9123-9484 0 PY - 2013 SN - 0094-2405 ST - Power spectrum analysis of the x-ray scatter signal in mammography and breast tomosynthesis projections T2 - Medical Physics TI - Power spectrum analysis of the x-ray scatter signal in mammography and breast tomosynthesis projections UR - ://WOS:000325394400021 VL - 40 ID - 206 ER - TY - JOUR AN - WOS:000336849900082 AU - Sechopoulos, I. AU - Fei, B. AU - Bliznakova, K. DA - Jun DO - 10.1118/1.4815665 M1 - 6 N1 - Times Cited: 0 0 PY - 2013 SN - 0094-2405 ST - Spatial Frequency Characterization of the X-Ray Scatter Signal in Breast Imaging T2 - Medical Physics TI - Spatial Frequency Characterization of the X-Ray Scatter Signal in Breast Imaging UR - ://WOS:000336849900082 VL - 40 ID - 209 ER - TY - JOUR AB - A nonrigid B-spline-based point-matching (BPM) method is proposed to match dense surface points. The method solves both the point correspondence and nonrigid transformation without features extraction. The registration method integrates a motion model, which combines a global transformation and a B-spline-based local deformation, into a robust point-matching framework. The point correspondence and deformable transformation are estimated simultaneously by fuzzy correspondence and by a deterministic annealing technique. Prior information about global translation, rotation and scaling is incorporated into the optimization. A local B-spline motion model decreases the degrees of freedom for optimization and thus enables the registration of a larger number of feature points. The performance of the BPM method has been demonstrated and validated using synthesized 2D and 3D data, mouse MRI and micro-CT images. The proposed BPM method can be used to register feature point sets, 2D curves, 3D surfaces and various image data. AN - WOS:000319966100023 AU - Wang, Hesheng AU - Fei, Baowei DA - Jun 21 DO - 10.1088/0031-9155/58/12/4315 M1 - 12 N1 - Times Cited: 4 Fei, Baowei /E-6898-2014 Fei, Baowei /0000-0002-9123-9484 0 4 PY - 2013 SN - 0031-9155 SP - 4315-4330 ST - Nonrigid point registration for 2D curves and 3D surfaces and its various applications T2 - Physics in Medicine and Biology TI - Nonrigid point registration for 2D curves and 3D surfaces and its various applications UR - ://WOS:000319966100023 VL - 58 ID - 208 ER - TY - JOUR AB - Background and objective Combined magnetic resonance/positron emission tomography (MR/PET) is a relatively new, hybrid imaging modality. MR-based attenuation correction often requires segmentation of the bone on MR images. In this study, we present an automatic segmentation method for the skull on MR images for attenuation correction in brain MR/PET applications. Materials and methods Our method transforms T1-weighted MR images to the Radon domain and then detects the features of the skull image. In the Radon domain we use a bilateral filter to construct a multiscale image series. For the repeated convolution we increase the spatial smoothing in each scale and make the width of the spatial and range Gaussian function doubled in each scale. Two filters with different kernels along the vertical direction are applied along the scales from the coarse to fine levels. The results from a coarse scale give a mask for the next fine scale and supervise the segmentation in the next fine scale. The use of the multiscale bilateral filtering schemeis to improve the robustness of the method for noise MR images. After combining the two filtered sinograms, the reciprocal binary sinogram of the skull is obtained for the reconstruction of the skull image. Results This method has been tested with brain phantom data, simulated brain data, and real MRI data. For real MRI data the Dice overlap ratios are 92.2%1.9% between our segmentation and manual segmentation. Conclusions The multiscale segmentation method is robust and accurate and can be used for MRI-based attenuation correction in combined MR/PET. AN - WOS:000325557600006 AU - Yang, Xiaofeng AU - Fei, Baowei DA - Nov DO - 10.1136/amiajnl-2012-001544 M1 - 6 N1 - Times Cited: 2 Fei, Baowei /E-6898-2014 Fei, Baowei /0000-0002-9123-9484 0 2 PY - 2013 SN - 1067-5027 SP - 1037-1045 ST - Multiscale segmentation of the skull in MR images for MRI-based attenuation correction of combined MR/PET T2 - Journal of the American Medical Informatics Association TI - Multiscale segmentation of the skull in MR images for MRI-based attenuation correction of combined MR/PET UR - ://WOS:000325557600006 VL - 20 ID - 205 ER - TY - JOUR AB - Photodynamic therapy is an emerging treatment modality that is under, intensive preclinical and clinical investigations for many types of disease including cancer. Despite the promise, there is a lack of a reliable drug delivery vehicle that can transport photosensitizers (PSs) to tumors in a site-specific manner: Previous efforts have been focused on polymer- or liposome-based nanocarriers, which are usually associated with a suboptimal PS loading rate and a large particle size. We report herein that a RGD4C-modified ferritin (RFRT), a protein-based nanoparticle, can serve as a safe and efficient PS vehicle. Zinc hexadecafluorophthalocyanine (ZnF16Pc), a potent PS with a high 102 quantum yield but poor water solubility, can be encapsulated into RFRTs with a loading rate as high as similar to 60 wt % (i.e, 13 mg of ZnF16Pc can be loaded on 1 mg of RAM), which far exceeds those reported previously.. Despite the high loading, the ZnF16Pc-loaded Fans (P-RFRTs) show an overall particle size of 18.6 +/- 2.6 nm, which is significantly smaller than other PS-nanocarrier conjugates: When tested on U87MG subcutaneous tumor models, P-RFRTs showed a high tumor accumulation rate (tumor-to-normal tissue ratio of 26.82 +/- 4.07at 24 h), a good tumor inhibition rate (8164% on day 12), as well as minimal toxicity to the skin and other major organs. This technology can be extended to deliver other metal-containing PSs and holds great clinical translation potential. AN - WOS:000323810600060 AU - Zhen, Zipeng AU - Tang, Wei AU - Guo, Cunlan AU - Chen, Hongmin AU - Lin, Xin AU - Liu, Gang AU - Fei, Baowei AU - Chen, Xiaoyuan AU - Xu, Binqian AU - Xie, Jin DA - Aug DO - 10.1021/nn402199g M1 - 8 N1 - Times Cited: 19 Guo, Cunlan/E-8077-2011; Fei, Baowei /E-6898-2014 Fei, Baowei /0000-0002-9123-9484 0 20 PY - 2013 SN - 1936-0851 SP - 6988-6996 ST - Ferritin Nanocages To Encapsulate and Deliver Photosensitizers for Efficient Photodynamic Therapy against Cancer T2 - Acs Nano TI - Ferritin Nanocages To Encapsulate and Deliver Photosensitizers for Efficient Photodynamic Therapy against Cancer UR - ://WOS:000323810600060 VL - 7 ID - 207 ER - TY - JOUR AB - A robust and accurate center-frequency (CF) estimation (RACE) algorithm for improving the performance of the local sine-wave modeling (SinMod) method, which is a good motion estimation method for tagged cardiac magnetic resonance (MR) images, is proposed in this study. The RACE algorithm can automatically, effectively and efficiently produce a very appropriate CF estimate for the SinMod method, under the circumstance that the specified tagging parameters are unknown, on account of the following two key techniques: (1) the well-known mean-shift algorithm, which can provide accurate and rapid CF estimation; and (2) an original two-direction-combination strategy, which can further enhance the accuracy and robustness of CF estimation. Some other available CF estimation algorithms are brought out for comparison. Several validation approaches that can work on the real data without ground truths are specially designed. Experimental results on human body in vivo cardiac data demonstrate the significance of accurate CF estimation for SinMod, and validate the effectiveness of RACE in facilitating the motion estimation performance of SinMod. (C) 2014 Elsevier Inc. All rights reserved. AN - WOS:000342546700010 AU - Liu, Hong AU - Wang, Jie AU - Xu, Xiangyang AU - Song, Enmin AU - Wang, Qian AU - Jin, Renchao AU - Hung, Chih-Cheng AU - Fei, Baowei DA - Nov DO - 10.1016/j.mri.2014.07.005 M1 - 9 N1 - Times Cited: 0 0 PY - 2014 SN - 0730-725X SP - 1139-1155 ST - A robust and accurate center-frequency estimation (RACE) algorithm for improving motion estimation performance of Sin Mod on tagged cardiac MR images without known tagging parameters T2 - Magnetic Resonance Imaging TI - A robust and accurate center-frequency estimation (RACE) algorithm for improving motion estimation performance of Sin Mod on tagged cardiac MR images without known tagging parameters UR - ://WOS:000342546700010 VL - 32 ID - 198 ER - TY - JOUR AB - Hyperspectral imaging (HSI) is an emerging imaging modality for medical applications, especially in disease diagnosis and image-guided surgery. HSI acquires a three-dimensional dataset called hypercube, with two spatial dimensions and one spectral dimension. Spatially resolved spectral imaging obtained by HSI provides diagnostic information about the tissue physiology, morphology, and composition. This review paper presents an overview of the literature on medical hyperspectral imaging technology and its applications. The aim of the survey is threefold: an introduction for those new to the field, an overview for those working in the field, and a reference for those searching for literature on a specific application. (C) The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI. AN - WOS:000331892700001 AU - Lu, Guolan AU - Fei, Baowei C7 - 010901 DA - Jan DO - 10.1117/1.jbo.19.1.010901 M1 - 1 N1 - Times Cited: 9 Fei, Baowei /E-6898-2014 Fei, Baowei /0000-0002-9123-9484 0 9 PY - 2014 SN - 1083-3668 ST - Medical hyperspectral imaging: a review T2 - Journal of Biomedical Optics TI - Medical hyperspectral imaging: a review UR - ://WOS:000331892700001 VL - 19 ID - 203 ER - TY - JOUR AB - Early detection of malignant lesions could improve both survival and quality of life of cancer patients. Hyperspectral imaging (HSI) has emerged as a powerful tool for noninvasive cancer detection and diagnosis, with the advantage of avoiding tissue biopsy and providing diagnostic signatures without the need of a contrast agent in real time. We developed a spectral-spatial classification method to distinguish cancer from normal tissue on hyperspectral images. We acquire hyperspectral reflectance images from 450 to 900 nm with a 2-nm increment from tumor-bearing mice. In our animal experiments, the HSI and classification method achieved a sensitivity of 93.7% and a specificity of 91.3%. The preliminary study demonstrated that HSI has the potential to be applied in vivo for noninvasive detection of tumors. (C) 2014 Society of Photo-Optical Instrumentation Engineers (SPIE) AN - WOS:000345837200021 AU - Lu, Guolan AU - Halig, Luma AU - Wang, Dongsheng AU - Qin, Xulei AU - Chen, Zhuo Georgia AU - Fei, Baowei C7 - 106004 DA - Oct DO - 10.1117/1.jbo.19.10.106004 M1 - 10 N1 - Times Cited: 0 0 PY - 2014 SN - 1083-3668 ST - Spectral-spatial classification for noninvasive cancer detection using hyperspectral imaging T2 - Journal of Biomedical Optics TI - Spectral-spatial classification for noninvasive cancer detection using hyperspectral imaging UR - ://WOS:000345837200021 VL - 19 ID - 199 ER - TY - JOUR AB - The aim of this study is to investigate the impact on image quality of using monochromatic beams for lower dose breast tomosynthesis (BT). For this purpose, modeling and simulation of BT and mammography imaging processes have been performed using two x-ray beams: one at 28 kVp and a monochromatic one at 19 keV at different entrance surface air kerma ranging between 0.16 and 5.5 mGy. Two 4 cm thick computational breast models, in a compressed state, were used: one simple homogeneous and one heterogeneous based on CT breast images, with compositions of 50% glandular-50% adipose and 40% glandular-60% adipose tissues by weight, respectively. Modeled lesions, representing masses and calcifications, were inserted within these breast phantoms. X-ray transport in the breast models was simulated with previously developed and validated Monte Carlo application. Results showed that, for the same incident photon fluence, the use of the monochromatic beam in BT resulted in higher image quality compared to the one using polychromatic acquisition, especially in terms of contrast. For the homogenous phantom, the improvement ranged between 15% and 22% for calcifications and masses, respectively, while for the heterogeneous one this improvement was in the order of 33% for the masses and 17% for the calcifications. For different exposures, comparable image quality in terms of signal-difference-to-noise ratio and higher contrast for all features was obtained when using a monochromatic 19 keV beam at a lower mean glandular dose, compared to the polychromatic one. Monochromatic images also provide better detail and, in combination with BT, can lead to substantial improvement in visualization of features, and particularly better edge detection of low-contrast masses. AN - WOS:000341379900015 AU - Malliori, A. AU - Bliznakova, K. AU - Sechopoulos, I. AU - Kamarianakis, Z. AU - Fei, B. AU - Pallikarakis, N. DA - Aug 21 DO - 10.1088/0031-9155/59/16/4681 M1 - 16 N1 - Times Cited: 1 0 1 PY - 2014 SN - 0031-9155 SP - 4681-4696 ST - Breast tomosynthesis with monochromatic beams: a feasibility study using Monte Carlo simulations T2 - Physics in Medicine and Biology TI - Breast tomosynthesis with monochromatic beams: a feasibility study using Monte Carlo simulations UR - ://WOS:000341379900015 VL - 59 ID - 200 ER - TY - JOUR AB - High-frequency ultrasound (HFU) has the ability to image both skeletal and cardiac muscles. The quantitative assessment of these myofiber orientations has a number of applications in both research and clinical examinations; however, difficulties arise due to the severe speckle noise contained in the HFU images. Thus, for the purpose of automatically measuring myofiber orientations from two-dimensional HFU images, we propose a two-step multiscale image decomposition method. It combines a nonlinear anisotropic diffusion filter and a coherence enhancing diffusion filter to extract myofibers. This method has been verified by ultrasound data from simulated phantoms, excised fiber phantoms, specimens of porcine hearts, and human skeletal muscles in vivo. The quantitative evaluations of both phantoms indicated that the myofiber measurements of our proposed method were more accurate than other methods. The myofiber orientations extracted from different layers of the porcine hearts matched the prediction of an established cardiac mode and demonstrated the feasibility of extracting cardiac myofiber orientations from HFU images ex vivo. Moreover, HFU also demonstrated the ability to measure myofiber orientations in vivo. AN - WOS:000338771300016 AU - Qin, Xulei AU - Fei, Baowei DA - Jul 21 DO - 10.1088/0031-9155/59/14/3907 M1 - 14 N1 - Times Cited: 1 0 1 PY - 2014 SN - 0031-9155 SP - 3907-3924 ST - Measuring myofiber orientations from high-frequency ultrasound images using multiscale decompositions T2 - Physics in Medicine and Biology TI - Measuring myofiber orientations from high-frequency ultrasound images using multiscale decompositions UR - ://WOS:000338771300016 VL - 59 ID - 201 ER - TY - JOUR AB - Photodynamic therapy (PDT) is a highly specific anticancer treatment modality for various cancers, particularly for recurrent cancers that no longer respond to conventional anticancer therapies. PDT has been under development for decades, but light-associated toxicity limits its clinical applications. To reduce the toxicity of PDT, we recently developed a targeted nanoparticle (NP) platform that combines a second-generation PDT drug, Pc 4, with a cancer targeting ligand, and iron oxide (IO) NPs. Carboxyl functionalized IO NPs were first conjugated with a fibronectin-mimetic peptide (Fmp), which binds integrin beta 1. Then the PDT drug Pc 4 was successfully encapsulated into the ligand-conjugated IO NPs to generate Fmp-IO-Pc 4. Our study indicated that both nontargeted IO-Pc 4 and targeted Fmp-IO-Pc 4 NPs accumulated in xenograft tumors with higher concentrations than nonfomiulated Pc 4. As expected, both IO-Pc 4 and Fmp-IO-Pc 4 reduced the size of HNSCC xenograft tumors more effectively than free Pc 4. Using a 10-fold lower dose of Pc 4 than that reported in the literature, the targeted Fmp-IO-Pc 4 NPs demonstrated significantly greater inhibition of tumor growth than nontargeted IO-Pc 4 NPs. These results suggest that the delivery of a PDT agent Pc 4 by IO NPs can enhance treatment efficacy and reduce PDT drug dose. The targeted IO-Pc 4 NPs have great potential to serve as both a magnetic resonance imaging (MRI) agent and PDT drug in the clinic. AN - WOS:000339463100016 AU - Wang, Dongsheng AU - Fei, Baowei AU - Halig, Luma V. AU - Qin, Xulei AU - Hu, Zhongliang AU - Xu, Hong AU - Wang, Yongqiang Andrew AU - Chen, Zhengjia AU - Kim, Sungjin AU - Shin, Dong M. AU - Chen, Zhuo DA - Jul DO - 10.1021/nn501652j M1 - 7 N1 - Times Cited: 2 0 2 PY - 2014 SN - 1936-0851 SP - 6620-6632 ST - Targeted Iron-Oxide Nanoparticle for Photodynamic Therapy and Imaging of Head and Neck Cancer T2 - Acs Nano TI - Targeted Iron-Oxide Nanoparticle for Photodynamic Therapy and Imaging of Head and Neck Cancer UR - ://WOS:000339463100016 VL - 8 ID - 202 ER -