Automatic segmentation of the colon for virtual colonoscopy

Virtual colonoscopy is a minimally invasive technique that enables early de tection of colorectal polyps and cancer. Normally, a patient's bowel is pre pared with colonic lavage and gas insufflation prior to computed tomography scanning. An important step for 3D analysis of the image volume is segment ation of the colon. The high-contrast gas/tissue interface that exists in t he colon lumen makes segmentation of the majority of the colon relatively e asy; however, two factors inhibit automatic segmentation of the entire colo n. First, the colon is not the only gas-filled organ in the data volume: lu ngs, small bowel, and stomach also meet this criterion. User-defined seed p oints placed in the colon lumen have previously been required to spatially isolate the colon. Second, portions of the colon lumen may be obstructed by peristalsis, large masses, and/or residual feces. These complicating facto rs require increased user interaction during the segmentation process to is olate additional colonic segments. To automate the segmentation of the colo n, we have developed a method to locate seed points and segment the gas-fil led lumen sections without user supervision. We have also developed an auto mated approach to improve lumen segmentation by digitally removing residual contrast-enhanced fluid. Experimental results with 20 patient volumes show that our method is accurate and reliable. (C) 2000 Elsevier Science Ltd. A ll rights reserved.