Computer-aided detection of polyps and masses for CT colonography

We are developing a computer-aided scheme for the detection of colonic polyps and masses in CT colonography. The colon is extracted automatically from CT images by use of a knowledge-guided technique. The detection of polyps and masses is based on shape index and curvedness features. A feature-guided segmentation technique is used to extract the regions of detected polyps. A quadratic discriminant classifier is used for reducing false-positive detections and for determining the final output based on shape index, gradient concentration; and CT value features. To evaluate the technique, we performed CT colonography for 72 patients with cleansed colons and by use of a standard technique with helical CT scanning. Thirteen patients had a total of 20 polyps measuring 5-12 mm, and four patients had 4 masses measuring 25-40 mm in diameter. In a by-polyp (by-mass) leave-one-out evaluation, the CAD scheme detected 95% of the polyps (all masses) with an average of 1.5 (0.5) false-positive detections per patient. These preliminary results suggest that our CAD scheme is potentially a useful tool for providing rapid interpretation and high diagnostic accuracy for CT colonography.