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A flexible machine learning image analysis system for high-precision computer-assisted segmentation of multispectral MRI data sets in patients with multiple sclerosis

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7 Author(s)
Wismuller, A. ; Dept. of Electr. & Comput. Eng., Florida State Univ., Tallahassee, FL ; Meyer-Baese, A. ; Behrends, J. ; Lange, O.
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Automatic brain segmentation is an issue of specific clinical relevance in both diagnosis and therapy control of patients with demyelinating diseases such as multiple sclerosis (MS). We present a complete system for high-precision computer-assisted image analysis of multispectral MRI data based on a flexible machine learning approach. Careful quality evaluation shows that the system outperforms conventional threshold-based techniques w.r.t. inter-observer agreement levels for the quantification of relevant clinical parameters, such as white matter lesion load and brain parenchyma volume

Published in:

Biomedical Imaging: Nano to Macro, 2006. 3rd IEEE International Symposium on

Date of Conference:

6-9 April 2006