Print Email Facebook Twitter Computer-Aided Detection of Polyps in CT Colonography Using Logistic Regression Title Computer-Aided Detection of Polyps in CT Colonography Using Logistic Regression Author Van Ravesteijn, V.F. Van Wijk, C. Vos, F.M. Truyen, R. Peters, J.F. Stoker, J. Van Vliet, L.J. Faculty Applied Sciences Department Imaging Science and Technology Date 2010-01-04 Abstract We present a computer-aided detection (CAD) system for computed tomography colonography that orders the polyps according to clinical relevance. TheCADsystem consists of two steps: candidate detection and supervised classification. The characteristics of the detection step lead to specific choices for the classification system. The candidates are ordered by a linear logistic classifier (logistic regression) based on only three features: the protrusion of the colon wall, the mean internal intensity, and a feature to discard detections on the rectal enema tube. This classifier can cope with a small number of polyps available for training, a large imbalance between polyps and non-polyp candidates, a truncated feature space, unbalanced and unknown misclassification costs, and an exponential distribution with respect to candidate size in feature space. Our CAD system was evaluated with data sets from four different medical centers. For polyps larger than or equal to 6mmwe achieved sensitivities of respectively 95%, 85%, 85%, and 100% with 5, 4, 5, and 6 false positives per scan over 86, 48, 141, and 32 patients. A cross-center evaluation in which the system is trained and tested with data from different sources showed that the trained CAD system generalizes to data from different medical centers and with different patient preparations. This is essential to application in large-scale screening for colorectal polyps. Subject computed tomography (CT) colonographycomputer aided diagnosislogistic regressionpattern recognitionpolyp detection To reference this document use: http://resolver.tudelft.nl/uuid:59fda6b8-8e93-4e20-847e-8b2aa2ae4da8 DOI https://doi.org/10.1109/TMI.2009.2028576 Publisher IEEE ISSN 0278-0062 Source IEEE Transactions on Medical Imaging, 29 (1), 2010 Part of collection Institutional Repository Document type journal article Rights (c) 2010 The Author(s); IEEE Files PDF vanRavesteijn_2010.pdf 1.03 MB Close viewer /islandora/object/uuid:59fda6b8-8e93-4e20-847e-8b2aa2ae4da8/datastream/OBJ/view