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 5-12mm, 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.

Date Published: 15 May 2003
PDF: 9 pages
Proc. SPIE 5032, Medical Imaging 2003: Image Processing, (15 May 2003); doi: 10.1117/12.481380

Published in SPIE Proceedings Vol. 5032:
Medical Imaging 2003: Image Processing
Milan Sonka; J. Michael Fitzpatrick, Editor(s)