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Assessment of an Optical Flow Field-Based Polyp Detector for CT colonography.

机译:用于CT结肠成像的基于光流场的息肉检测器的评估。

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Most current computer-aided detection (CAD) algorithms for the fully automatic detection of colonic polyps from 3D CT data suffer from high false positive rates. We developed and evaluated a post-processing algorithm to decrease the false positive rate of such a method. Our method attempts to model the way a radiologist recognizes a polyp while scrolling a cross-sectional plane through 3D CT data by quantifying the change in location of the edges in 2D plane. It uses a classifier for identification base on the Mahalanobis distance. The new method increase the ROC curve area from 0.89 to 0.98 (an increase from 34.5% to 85.0% in specificity for 100% sensitivity) in a population of 8 patients.

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