Automated segmentation of MS lesions from multi-channel MR images

van Leemput, Koen and Maes, Frederik and Bello, Fernando and Vandermeulen, Dirk and Colchester, Alan C. F. and Suetens, Paul (1999) Automated segmentation of MS lesions from multi-channel MR images. In: 2nd International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 99), Sep 19-22, 1999, Cambridge, England. (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

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Quantitative analysis of AIR images is becoming increasingly important as a surrogate marker in clinical trials in multiple sclerosis (MS). This paper describes a fully automated model-based method for segmentation of MS lesions from multi-channel AIR images. The method simultaneously corrects for AIR field inhomogeneities, estimates tissue class distribution parameters and classifies the image voxels. MS lesions are detected as voxels that are not well explained by the model. The results of the automated method are compared with the lesions delineated by human experts, showing a significant total lesion load correlation and an average overall spatial correspondence similar to that between the experts.

Item Type: Conference or workshop item (Paper)
Additional information: Proceedings Paper
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 75 Electronic computers. Computer science
T Technology > TA Engineering (General). Civil engineering (General) > TA1637 Image Analysis, Image Processing
Divisions: Faculties > Science Technology and Medical Studies > School of Engineering and Digital Arts
Depositing User: F.D. Zabet
Date Deposited: 19 Mar 2009 13:22
Last Modified: 14 May 2014 13:49
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