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Proceedings Paper

Fusing Markov random fields with anatomical knowledge and shape-based analysis to segment multiple sclerosis white matter lesions in magnetic resonance images of the brain
Author(s): Stephan AlZubi; Klaus D. Toennies; N. Bodammer; Herman Hinrichs
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Paper Abstract

This paper proposes an image analysis system to segment multiple sclerosis lesions of magnetic resonance (MR) brain volumes consisting of 3 mm thick slices using three channels (images showing T1-, T2- and PD -weighted contrast). The method uses the statistical model of Markov Random Fields (MRF) both at low and high levels. The neighborhood system used in this MRF is defined in three types: (1) Voxel to voxel: a low-level heterogeneous neighborhood system is used to restore noisy images. (2) Voxel to segment: a fuzzy atlas, which indicates the probability distribution of each tissue type in the brain, is registered elastically with the MRF. It is used by the MRF as a-priori knowledge to correct miss-classified voxels. (3) Segment to segment: Remaining lesion candidates are processed by a feature based classifier that looks at unary and neighborhood information to eliminate more false positives. An expert's manual segmentation was compared with the algorithm.

Paper Details

Date Published: 9 May 2002
PDF: 10 pages
Proc. SPIE 4684, Medical Imaging 2002: Image Processing, (9 May 2002); doi: 10.1117/12.467160
Show Author Affiliations
Stephan AlZubi, Otto-von-Guericke Univ. Magdeburg (Germany)
Klaus D. Toennies, Otto-von-Guericke Univ. Magdeburg (Germany)
N. Bodammer, Otto-von-Guericke Univ. Magdeburg (Germany)
Herman Hinrichs, Otto-von-Guericke Univ. Magdeburg (Germany)


Published in SPIE Proceedings Vol. 4684:
Medical Imaging 2002: Image Processing
Milan Sonka; J. Michael Fitzpatrick, Editor(s)

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