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Shape filtering for false positive reduction at computed tomography colonography

Miranda, Abhilash A., Chowdhury, Tarik A., Ghita, Ovidiu and Whelan, Paul F. orcid logoORCID: 0000-0001-9230-7656 (2006) Shape filtering for false positive reduction at computed tomography colonography. In: MICCAI 2006 - 9th International Conference on Medical Image Computing and Computer-Assisted Intervention, 1-6 October 2006, Copenhagen, Denmark. ISBN 978-3-540-44727-6

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.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Uncontrolled Keywords:image analysis; Computer Aided Detection in Computed Tomography Colonography (CAD-CTC);
Subjects:UNSPECIFIED
DCU Faculties and Centres:Research Initiatives and Centres > Research Institute for Networks and Communications Engineering (RINCE)
Published in: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2006. Lecture Notes in Computer Science 4191. Springer Berlin / Heidelberg. ISBN 978-3-540-44727-6
Publisher:Springer Berlin / Heidelberg
Official URL:http://dx.doi.org/10.1007/11866763_11
Copyright Information:The original publication is available at www.springerlink.com
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:4664
Deposited On:03 Jul 2009 09:49 by DORAS Administrator . Last Modified 11 Jan 2019 16:08
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