Abstract
Electronic colon cleansing (ECC) aims to segment the colon lumen from the patient abdominal image acquired with colonic material tagging by oral contrast and other means, so that a virtual colon model can be constructed. Virtual colonoscopy (VC) navigates through the colon model looking for polyps in a similar manner as the fiber optic colonoscopy does. We had built an ECC pipeline for the commercial VC system of Viatronix Inc. In this paper, we present an improved ECC method. It is based on a partial -volume image -segmentation framework, which is derived using the well-established statistical expectation-maximization algorithm. The presented ECC method was evaluated by both visual inspection on the cleansed colon lumens and computer-aided detection of polyps (CADpolyp) using 20 patient datasets. Compared to our previous ECC pipeline, this presented new method demonstrates improvement in both visual judgment and CADpolyp.
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