Computer-aided detection of polyps in optical colonoscopy images

Saad Nadeem; Arie Kaufman

doi:10.1117/12.2216996

24 March 2016 Computer-aided detection of polyps in optical colonoscopy images

Saad Nadeem, Arie Kaufman

Proceedings Volume 9785, Medical Imaging 2016: Computer-Aided Diagnosis; 978525 (2016) https://doi.org/10.1117/12.2216996
Event: SPIE Medical Imaging, 2016, San Diego, California, United States

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%.

Citation Download Citation

Saad Nadeem and Arie Kaufman "Computer-aided detection of polyps in optical colonoscopy images", Proc. SPIE 9785, Medical Imaging 2016: Computer-Aided Diagnosis, 978525 (24 March 2016); https://doi.org/10.1117/12.2216996

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