Computer-aided diagnosis scheme for detection of polyps at CT colonography.

Abstract

Colon cancer is one of the leading causes of cancer deaths in the United States. However, most colon cancers can be prevented if precursor colonic polyps are detected and removed. An advanced computer-aided diagnosis (CAD) scheme was developed for the automated detection of polyps at computed tomographic (CT) colonography. A region encompassing the colonic wall is extracted from an isotropic volume data set obtained by interpolating CT colonographic scans along the axial direction. Polyp candidates are detected with computation of three-dimensional (3D) geometric features that characterize polyps, followed by extraction of polyps with hysteresis thresholding and fuzzy clustering using these geometric features. The number of false-positive findings is reduced by extracting 3D texture features from polyp candidates and applying quadratic discriminant analysis to the candidates. This CAD scheme was applied in 71 patients who underwent CT colonography, 14 of whom had colonoscopically confirmed polyps (n = 21). At by-patient analysis, sensitivity was 100%, with an average false-positive rate of 2.0 per patient. At by-polyp analysis, the scheme detected 90% of the polyps at the same false-positive rate. This CAD scheme permits accurate detection of suspicious lesions and thus has the potential to reduce radiologists' interpretation time and improve their diagnostic accuracy in the detection of polyps at CT colonography.