Ms-lesion Segmentation in Mri with Random Forests
نویسندگان
چکیده
Multiple sclerosis (MS) is a common autoimmune disorder, whose diagnosis and study often relies on the extraction of biomarkers from magnetic resonance imaging (MRI) scans. Manual segmentation of MS lesions suffers from large intraand inter-rater differences, whereas automatic methods promise reproducibility and enhanced consistency, especially for tracking the disease progress over time. To test this claim, the ISBI 2015 Longitudinal MS Lesion Segmentation Challenge provides a platform to compare existing methods in a fair and consistent manner to each other and the manual approach. In this article, we present our challenge contribution, which is based on random forests and local context intensity features to segment MS lesions in multi-spectral MRI images.
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