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Ranking of polyp candidates for CAD in CT colonography

We investigated the application of optimized ranking schemes in the analysis of polyp candidates detected from CT colonography datasets by our CAD scheme. CT colonography was performed for 28 patients in supine and prone positions with a standard pre-colonoscopy preparation and air distension. There were 42 colonoscopy-confirmed polyps 5-25 mm in size. The colons were extracted by use of a centerline-based colon segmentation technique. Polyp candidates were detected from the extracted region of colonic wall by use of geometric features sensitive to polypoid shapes. The by-polyp detection sensitivity was 98%. The detected polyp candidates were ranked based on a ranking function constructed from a linear combination of polyp features. The feature weights were optimized by a downhill simplex method by maximizing the rank of the lowest-ranking true-positive polyp candidate. We considered two types of ranking: by-dataset ranking and global ranking. The most effective ranking functions included multiple features and could reduce the amount of initially detected polyp candidates by 56% without compromising the high by-polyp detection sensitivity. The ranking schemes may be useful in optimizing the performance of CAD schemes for the detection of polyps in CT colonography.