In Multiple Sclerosis (MS), detection of T2-hyperintense white matter lesions on MRI has become a crucial criterion for early diagnosis and monitoring. In this study, we propose an accurate and reliable automated method for lesion segmentation and longitudinal follow-up, using color-scaled maps of lesion evolution depicting increasing and decreasing patterns. Validation of the cross-sectional segmentation has been performed on large samples of MS patients and shows good agreement with manual tracing. Through its reliability and robustness, the measures provided by our automated method of lesion quantification could be a valuable tool for clinical routine and clinical trials.
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