複素自己回帰モデルによる凹領域認識を用いた大腸ポリープ像の自動検出

概要

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We have been developing a computer-aided detection (CAD) system for detecting colonic polyps in CT colonography. The CAD scheme consists of the following two main steps: (1) producing cross-sectional images along a centerline of colon region and (2) detecting colonic polyps based on the complex autoregressive model for recognition of concave areas. In this paper, we describe an experimental result in applying complex partial correlation (PARCOR) coefficient to CT colonography and evaluate the CAD performance. As an initial result, the sensitivity was 82% (9/11) with 184 false positives (FPs) per case in 7 clinical cases, which indicates that our proposed method may be effective for polyp detection but the issue of existing FP candidates has to be solved in the next step.
医用画像情報学会の論文
2004-01-01