Detection of anatomical landmarks in human colon from computed tomographic colonography images

Colon cancer is the second leading cause of cancer-related deaths per year in industrial nations. Virtual colonoscopy is a new, less invasive alternative to the usually practiced optical colonoscopy for colorectal polyp and cancer screening. In this paper, we present some physics-based modeling and pattern recognition techniques to identify anatomical landmarks in the human colon like the haustral folds and the tenia coli to further exploit the benefits of virtual colonoscopy. A combination of heat diffusion field algorithm and fuzzy c-means clustering algorithm is used to detect the haustral folds in human colon from volumetric computed tomography (CT) images. Each voxel on the corresponding colon surface is parameterized using the colon centerline information and associated local Frenet frames. The parameterized fold information is utilized to establish the tentative location of one tenia coli. Preliminary results on automated detection of tenia coli are shown on the colon surface.