Computer Aided Detection for CT Colonography

$0ZIAFY2015CLNIH

Clinical Center

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Abstract

We are improving CT colonography (virtual colonoscopy) by developing computer-assisted diagnosis methods. These methods attempt to identify and characterize colonic polyps automatically, thereby increasing physician accuracy and efficiency and helping patients by finding their polyps. We made a number of advances over the past year. We showed that pericolonic visceral fat is a more useful predictive risk factor for colonic polyps compared with the more routinely used pan-abdominal visceral fat measurements. We are developing methods to detect extracolonic findings on CT colonography using fully-automated software. We improved the accuracy of computer-aided polyp detection using recent advances in machine learning.

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