Shape filtering for false positive reduction at computed tomography colonography

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Abstract

In this paper, we treat the problem of reducing the false positives (FP) in the automatic detection of colorectal polyps at Computer Aided Detection in Computed Tomography Colonography (CAD-CTC) as a shape-filtering task. From the extracted candidate surface, we obtain a reliable shape distribution function and analyse it in the Fourier domain and use the resulting spectral data to classify the candidate surface as belonging to a polyp or a non-polyp class. The developed shape filtering scheme is computationally efficient (takes approximately 2 seconds per dataset to detect the polyps from the colonic surface) and offers robust polyp detection with an overall false positive rate of 5.44 per dataset at a sensitivity of 100% for polyps greater than 10mm when it was applied to standard and low dose CT data. © Springer-Verlag Berlin Heidelberg 2006.

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Miranda, A. A., Chowdhury, T. A., Ghita, O., & Whelan, P. F. (2006). Shape filtering for false positive reduction at computed tomography colonography. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4191 LNCS-II, pp. 84–92). Springer Verlag. https://doi.org/10.1007/11866763_11

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