van Leemput, Koen, Maes, Frederik, Bello, Fernando, Vandermeulen, Dirk, Colchester, Alan C. F., Suetens, Paul (1999) Automated segmentation of MS lesions from multi-channel MR images. In: Taylor, Chris and Colchester, Alan C. F., eds. Medical Image Computing and Computer-Assisted Intervention, MICCAI'99, Proceedings. Lecture Notes in Computer Science , 1679. pp. 11-21. Springer-Verlag Berlin ISBN 3-540-66503-X. (doi:10.1007/10704282_2) (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) (KAR id:16705)
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. | |
Official URL: http://dx.doi.org/10.1007/10704282_2 |
Abstract
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) |
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DOI/Identification number: | 10.1007/10704282_2 |
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 processing |
Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts |
Depositing User: | F.D. Zabet |
Date Deposited: | 19 Mar 2009 13:22 UTC |
Last Modified: | 05 Nov 2024 09:51 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/16705 (The current URI for this page, for reference purposes) |
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