Enhanced detection in CT colonography using adaptive diffusion filtering

Douiri, A., Siddique, M., Ye, X., Beddoe, G. & Slabaugh, G.G. (2009). Enhanced detection in CT colonography using adaptive diffusion filtering. Progress in Biomedical Optics and Imaging - Proceedings of SPIE, 7259, p. 725923. doi: 10.1117/12.811563

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Abstract

Computer-aided detection (CAD) is a computerized procedure in medical science that supports the medical team’s interpretations and decisions. CAD uses information from a medical imaging modality such as Computed Tomography to detect suspicious lesions. Algorithms to detect these lesions are based on geometrical models which can describe the local structures and thus provide potential region candidates. Geometrical descriptive models are very dependent on the data quality which may affect the false positive rates in CAD. In this paper we propose an efficient adaptive diffusion technique that adaptively controls the diffusion flux of the local structures in the data using robust statistics. The proposed method acts isotropically in the homogeneous regions and anisotropically in the vicinity of jump discontinuities. This method structurally enhances the data and makes the geometrical descriptive models robust. For the iterative solver, we use an efficient gradient descent flows solver based on a PDE formulation of the problem. The whole proposed strategy, which makes use of adaptive diffusion filter coupled with gradient descent flows has been developed and evaluated on clinical data in the application to colonic polyp detection in Computed Tomography Colonoscopy.

Item Type: Article
Additional Information: Copyright (2009) Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.
Uncontrolled Keywords: Diffusion ; Virtual colonoscopy ; Medical imaging modalities ; Algorithms ; Colon ; Computed tomography ; Computer-aided diagnosis
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
R Medicine > RC Internal medicine
Divisions: School of Informatics > Department of Computing
URI: http://openaccess.city.ac.uk/id/eprint/4382

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