A novel colonic polyp volume segmentation method for computer tomographic colonography

Colorectal cancer is the third most common type of cancer. However, this disease can be prevented by detection and removal of precursor adenomatous polyps after the diagnosis given by experts on computer tomographic colonography (CTC). During CTC diagnosis, the radiologist looks for colon polyps and measures not only the size but also the malignancy. It is a common sense that to segment polyp volumes from their complicated growing environment is of much significance for accomplishing the CTC based early diagnosis task. Previously, the polyp volumes are mainly given from the manually or semi-automatically drawing by the radiologists. As a result, some deviations cannot be avoided since the polyps are usually small (6~9mm) and the radiologistsa' experience and knowledge are varying from one to another. In order to achieve automatic polyp segmentation carried out by the machine, we proposed a new method based on the colon decomposition strategy. We evaluated our algorithm on both phantom and patient data. Experimental results demonstrate our approach is capable of segment the small polyps from their complicated growing background.