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Publication Detail
Topologically correct cortical segmentation using Khalimsky's cubic complex framework
  • Publication Type:
    Conference
  • Authors:
    Cardoso MJ, Clarkson MJ, Modat M, Talbot H, Couprie M, Ourselin S
  • Publication date:
    09/06/2011
  • Published proceedings:
    Progress in Biomedical Optics and Imaging - Proceedings of SPIE
  • Volume:
    7962
  • ISBN-13:
    9780819485045
  • Status:
    Published
  • Print ISSN:
    1605-7422
Abstract
Automatic segmentation of the cerebral cortex from magnetic resonance brain images is a valuable tool for neuroscience research. Due to the presence of noise, intensity non-uniformity, partial volume effects, the limited resolution of MRI and the highly convoluted shape of the cerebral cortex, segmenting the brain in a robust, accurate and topologically correct way still poses a challenge. In this paper we describe a topologically correct Expectation Maximisation based Maximum a Posteriori segmentation algorithm formulated within the Khalimsky cubic complex framework, where both the solution of the EM algorithm and the information derived from a geodesic distance function are used to locally modify the weighting of a Markov Random Field and drive the topology correction operations. Experiments performed on 20 Brainweb datasets show that the proposed method obtains a topologically correct segmentation without significant loss in accuracy when compared to two well established techniques. © 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).
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Dept of Med Phys & Biomedical Eng
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