The paper presents a system for Computer Aided Detection in Virtual Colonography based on geometric modeling. We label locations in the CT volume data, which have a high probability of being colonic polyps, and present them in a user-friendly way. We introduce a method for fast colonic wall elimination and then model polyps based on Slope Density Functions, to be able to reduce the number of false positive cases. The method was tested on a study group of 50 data sets. Using normal colonoscopy as standard of reference, true positive and false positive findings were determined. The detection rate for polyps larger than 6mm was above 85%. Initial results show that Computer Aided Diagnosis is feasible and that our method holds potential for screening purposes. © Springer-Verlag Berlin Heidelberg 2003.
CITATION STYLE
Kiss, G., Van Cleynenbreugel, J., Suetens, P., & Marchal, G. (2003). Computer aided diagnosis for CT colonography via slope density functions. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2878, 746–753. https://doi.org/10.1007/978-3-540-39899-8_91
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