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Proceedings Paper

Computer-aided detection of polyps in optical colonoscopy images
Author(s): Saad Nadeem; Arie Kaufman
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Paper Abstract

We present a computer-aided detection algorithm for polyps in optical colonoscopy images. Polyps are the precursors to colon cancer. In the US alone, 14 million optical colonoscopies are performed every year, mostly to screen for polyps. Optical colonoscopy has been shown to have an approximately 25% polyp miss rate due to the convoluted folds and bends present in the colon. In this work, we present an automatic detection algorithm to detect these polyps in the optical colonoscopy images. We use a machine learning algorithm to infer a depth map for a given optical colonoscopy image and then use a detailed pre-built polyp profile to detect and delineate the boundaries of polyps in this given image. We have achieved the best recall of 84.0% and the best specificity value of 83.4%.

Paper Details

Date Published: 24 March 2016
PDF: 12 pages
Proc. SPIE 9785, Medical Imaging 2016: Computer-Aided Diagnosis, 978525 (24 March 2016); doi: 10.1117/12.2216996
Show Author Affiliations
Saad Nadeem, Stony Brook Univ. (United States)
Arie Kaufman, Stony Brook Univ. (United States)

Published in SPIE Proceedings Vol. 9785:
Medical Imaging 2016: Computer-Aided Diagnosis
Georgia D. Tourassi; Samuel G. Armato III, Editor(s)

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