Efficient detection of polyps in CT colonography

Matthias Wolf; Pascal Cathier; Sarang Lakare; Murat Dundar; Luca Bogoni

doi:10.1117/12.709734

29 March 2007 Efficient detection of polyps in CT colonography

Matthias Wolf, Pascal Cathier, Sarang Lakare, Murat Dundar, Luca Bogoni

Proceedings Volume 6514, Medical Imaging 2007: Computer-Aided Diagnosis; 651408 (2007) https://doi.org/10.1117/12.709734
Event: Medical Imaging, 2007, San Diego, CA, United States

Abstract

Colon cancer is a widespread disease and, according to the American Cancer Society, it is estimated that in 2006 more than 55,000 people will die of colon cancer in the US. However, early detection of colorectal polyps helps to drastically reduces mortality. Computer-Aided Detection (CAD) of colorectal polyps is a tool that could help physicians finding such lesions in CT scans of the colon. In this paper, we present the first phase, candidate generation (CG), of our technique for the detection of colonic polyp candidate locations in CT colonoscopy. Since polyps typically appear as protrusions on the surface of the colon, our cutting-plane algorithm identifies all those areas that can be "cut-off" using a plane. The key observation is that for any protruding lesion there is at least one plane that cuts a fragment off. Furthermore, the intersection between the plane and the polyp will typically be small and circular. On the other hand, a plane cannot cut a small circular cross-section from a wall or a fold, due to their concave or elongated paraboloid morphology, because these structures yield cross-sections that are much larger or non-circular. The algorithm has been incorporated as part of a prototype CAD system. An analysis on a test set of more than 400 patients yielded a high per-patient sensitivity of 95% and 90% in clean and tagged preparation respectively for polyps ranging from 6mm to 20mm in size.

Citation Download Citation

Matthias Wolf, Pascal Cathier, Sarang Lakare, Murat Dundar, and Luca Bogoni "Efficient detection of polyps in CT colonography", Proc. SPIE 6514, Medical Imaging 2007: Computer-Aided Diagnosis, 651408 (29 March 2007); https://doi.org/10.1117/12.709734

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