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Proceedings Paper

Computer-aided detection of colonic polyps using volume rendering
Author(s): Wei Hong; Feng Qiu; Joseph Marino; Arie Kaufman
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Paper Abstract

This work utilizes a novel pipeline for the computer-aided detection (CAD) of colonic polyps, assisting radiologists in locating polyps when using a virtual colonoscopy system. Our CAD pipeline automatically detects polyps while reducing the number of false positives (FPs). It integrates volume rendering and conformal colon flattening with texture and shape analysis. The colon is first digitally cleansed, segmented, and extracted from the CT dataset of the abdomen. The colon surface is then mapped to a 2D rectangle using conformal mapping. Using this colon flattening method, the CAD problem is converted from 3D into 2D. The flattened image is rendered using a direct volume rendering of the 3D colon dataset with a translucent transfer function. Suspicious polyps are detected by applying a clustering method on the 2D volume rendered image. The FPs are reduced by analyzing shape and texture features of the suspicious areas detected by the clustering step. Compared with shape-based methods, ours is much faster and much more efficient as it avoids computing curvature and other shape parameters for the whole colon wall. We tested our method with 178 datasets and found it to be 100% sensitive to adenomatous polyps with a low rate of FPs. The CAD results are seamlessly integrated into a virtual colonoscopy system, providing the radiologists with visual cues and likelihood indicators of areas likely to contain polyps, and allowing them to quickly inspect the suspicious areas and further exploit the flattened colon view for easy navigation and bookmark placement.

Paper Details

Date Published: 29 March 2007
PDF: 9 pages
Proc. SPIE 6514, Medical Imaging 2007: Computer-Aided Diagnosis, 651406 (29 March 2007); doi: 10.1117/12.710022
Show Author Affiliations
Wei Hong, Stony Brook Univ. (United States)
Feng Qiu, Stony Brook Univ. (United States)
Joseph Marino, Stony Brook Univ. (United States)
Arie Kaufman, Stony Brook Univ. (United States)


Published in SPIE Proceedings Vol. 6514:
Medical Imaging 2007: Computer-Aided Diagnosis
Maryellen L. Giger; Nico Karssemeijer, Editor(s)

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