Surface normal overlap: a computer-aided detection algorithm with application to colonic polyps and lung nodules in helical CT.

David S Paik; Christopher F Beaulieu; Geoffrey D Rubin; Burak Acar; R Brooke Jeffrey; Judy Yee; Joyoni Dey; Sandy Napel

doi:10.1109/tmi.2004.826362

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Surface normal overlap: a computer-aided detection algorithm with application to colonic polyps and lung nodules in helical CT.

David S Paik·Christopher F Beaulieu·Geoffrey D Rubin·Burak Acar·R Brooke Jeffrey·Judy Yee·Joyoni Dey·Sandy Napel

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Abstract

We developed a novel computer-aided detection (CAD) algorithm called the surface normal overlap method that we applied to colonic polyp detection and lung nodule detection in helical computed tomography (CT) images. We demonstrate some of the theoretical aspects of this algorithm using a statistical shape model. The algorithm was then optimized on simulated CT data and evaluated using a per-lesion cross-validation on 8 CT colonography datasets and on 8 chest CT datasets. It is able to achieve 100% sensitivity for colonic polyps 10 mm and larger at 7.0 false positives (FPs)/dataset and 90% sensitivity for solid lung nodules 6 mm and larger at 5.6 FP/dataset.

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Algorithms Colonic Polyps Databases, Factual Humans Imaging, Three-Dimensional Pattern Recognition, Automated Phantoms, Imaging Radiographic Image Interpretation, Computer-Assisted Reproducibility of Results Retrospective Studies Sensitivity and Specificity Single-Blind Method Solitary Pulmonary Nodule Tomography, Spiral Computed Comparative Study Evaluation Study Journal Article Research Support, U.S. Gov't, P.H.S.Validation Study

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David S Paik, Christopher F Beaulieu, Geoffrey D Rubin, Burak Acar, R Brooke Jeffrey, Judy Yee, Joyoni Dey, Sandy Napel. 2004. Surface normal overlap: a computer-aided detection algorithm with application to colonic polyps and lung nodules in helical CT.. https://doi.org/10.1109/tmi.2004.826362

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