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Surface normal overlap: A computer-aided detection algorithm, with application to colonic polyps and lung nodules in helical CT IEEE TRANSACTIONS ON MEDICAL IMAGING Paik, D. S., Beaulieu, C. F., Rubin, G. D., Acar, B., Jeffrey, R. B., Yee, J., Dey, J., Napel, S. 2004; 23 (6): 661-675

Abstract

We developed a novel computer-aided detection (CAD) algorithm called the surface normal overlap method that we applied to colonic polyp detection and lung nodule detection in helical computed tomography (CT) images. We demonstrate some of the theoretical aspects of this algorithm using a statistical shape model. The algorithm was then optimized on simulated CT data and evaluated using a per-lesion cross-validation on 8 CT colonography datasets and on 8 chest CT datasets. It is able to achieve 100% sensitivity for colonic polyps 10 mm and larger at 7.0 false positives (FPs)/dataset and 90% sensitivity for solid lung nodules 6 mm and larger at 5.6 FP/dataset.

View details for DOI 10.1109/TMI.2004.826362

View details for Web of Science ID 000221723600001

View details for PubMedID 15191141