Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
Computing the differential characteristics of isointensity surface
Computer Vision and Image Understanding
Combining mesh, volume, and streamline representations for polyp detection in CT colonography
ISBI'09 Proceedings of the Sixth IEEE international conference on Symposium on Biomedical Imaging: From Nano to Macro
A probabilistic model for haustral curvatures with applications to colon CAD
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention
Feature selection using mutual information in CT colonography
Pattern Recognition Letters
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A novel approach for generating a set of features derived from properties of patterns of curvature is introduced as a part of a computer aided colonic polyp detection system. The resulting sensitivity was 84% with 4.8 false positives per volume on an independent test set of 72 patients (56 polyps). When used in conjunction with other features, it allowed the detection system to reach an overall sensitivity of 94% with a false positive rate of 4.3 per volume.