Abstract
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.
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Wismüller, A. et al. (2003). High-Precision Computer-Assisted Segmentation of Multispectral MRI Data Sets in Patients with Multiple Sclerosis by a Flexible Machine Learning Image Analysis Approach. In: Wittenberg, T., Hastreiter, P., Hoppe, U., Handels, H., Horsch, A., Meinzer, HP. (eds) Bildverarbeitung für die Medizin 2003. Informatik aktuell. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-18993-7_82
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DOI: https://doi.org/10.1007/978-3-642-18993-7_82
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-00619-0
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