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3 March 2008 Effect of 3D automated prostate segmentation for ultrasound image guided repeat biopsy application
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Proceedings Volume 6812, Image Processing: Algorithms and Systems VI; 68121A (2008) https://doi.org/10.1117/12.766991
Event: Electronic Imaging, 2008, San Jose, California, United States
Abstract
Prostate repeat biopsy has become one of the key requirements in today's prostate cancer detection. Urologists are interested in knowing previous 3-D biopsy locations during the current visit of the patient. Eigen has developed a system for performing 3-D Ultrasound image guided prostate biopsy. The repeat biopsy tool consists of three stages: (1) segmentation of the prostate capsules from previous and current ultrasound volumes; (2) registration of segmented surfaces using adaptive focus deformable model; (3) mapping of old biopsy sites onto new volume via thin-plate splines (TPS). The system critically depends on accurate 3-D segmentation of capsule volumes. In this paper, we study the effect of automated segmentation technique on the accuracy of 3-D ultrasound guided repeat biopsy. Our database consists of 38 prostate volumes of different patients which are acquired using Philips sidefire transrectal ultrasound (TRUS) probe. The prostate volumes were segmented in three ways: expert segmentation, semi-automated segmentation, and fully automated segmentation. New biopsy sites were identified in the new volumes from different segmentation methods, and we compared the mean squared distance between biopsy sites. It is demonstrated that the performance of our fully automated segmentation tool is comparable to that of semi-automated segmentation method.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yujun Guo, Lu Li, Ramakrishnan Narayanan, Dinesh Kumar, Albaha Barqawi, E. David Crawford, and Jasjit S. Suri "Effect of 3D automated prostate segmentation for ultrasound image guided repeat biopsy application", Proc. SPIE 6812, Image Processing: Algorithms and Systems VI, 68121A (3 March 2008); https://doi.org/10.1117/12.766991
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