VISION-LIST Digest Tue Jul 25 15:14:41 PDT 95 Volume 14 : Issue 28 - ***** The Vision List host is TELEOS.COM ***** - Send submissions to Vision-List@TELEOS.COM - Vision List Digest available via COMP.AI.VISION newsgroup - If you don't have access to COMP.AI.VISION, request list membership to Vision-List-Request@TELEOS.COM - Access Vision List Archives via anonymous ftp to TELEOS.COM ... Date: Mon, 17 Jul 1995 00:12:17 GMT From: William Katz Organization: Virginia Neurologic Institute Subject: Medical Imaging/3D Image Analysis Lectures Starting 7/17 There will be a series of talks for the next three mondays (July 17, July 24, July 31) on a variety of topics within medical imaging and three-dimensional image analysis. The lectures are invited applicants for the Director of the Neurosurgical Visualization Laboratory within the Dept. of Neurosurgery. All lectures will be held at Camp Heart Auditorium, 4th floor of the New Hospital at Univ. of Virginia. Talks will be approximately 40-50 minutes with some time leftover for questions. Monday, July 17, 1995 Speaker: Zhenyu Wu, Ph.D. Topic: Image Analysis of 3D Magnetic Resonance Microscopic Images using Subvoxel Segmentation and Bayesian Modeling. Time: 3:30 pm NMR microscopy is currently being used as an investigational tool for the evaluation of micromorphometric parameters of trabecular bone as a possible means to assess its strength. Since, typically, the image voxel size is not significantly smaller than individual trabecular elements, partial volume blurring can be a major complication for accurate tissue classification. In this paper, a Bayesian segmentation technique is reported that achieves improved subvoxel tissue classification. Each voxel is subdivided either into eight subvoxels twice the original resolution, or up to four subvoxels along the transaxial direction and the subvoxels optimally classified as either bone or marrow. Based on a statistical model for partial volume blurring, the likelihood for the number of marrow subvoxels in each voxel can be computed on the basis of its measured signal. To resolve the ambiguity of the location of the marrow subvoxels, a Gibbs distribution is introduced to model the interaction between the subvoxels. Neighboring subvoxel pairs with the same tissue label are encouraged, and pairs with distinct labels are penalized. The segmentation is achieved by maximizing the a posteriori probability of the label image using the block ICM (iterative conditional mode) algorithm. The potential of the proposed technique is demonstrated in real and synthetic NMR microscopic images. Key words: Tissue classification, NMR microscopy, partial voluming, trabecular bone.