Yi Gao, Romeil Sandhu, Gabor Fichtinger, and Allen Tannenbaum
Medical Imaging, IEEE Transactions on 29.10 (2010): 1781-1794.
Publication year: 2010

Extracting the prostate from magnetic resonance (MR) imagery is a challenging and important task for medical image analysis and surgical planning. We present in this work a unified shape-based framework to extract the prostate from MR prostate imagery. In many cases, shape-based segmentation is a two-part problem. First, one must properly align a set of training shapes such that any variation in shape is not due to pose. Then segmentation can be performed under the constraint of the learnt shape. We provide experimental results, which include several challenging clinical data sets, to highlight the algorithm’s capability of robustly handling supine/prone prostate registration and the overall segmentation task