Aim of the study was to adapt and evaluate on FLAIR images a recently developed semi-automatic method for segmentation of hyperintense multiple sclerosis (MS) lesions on dual-echo (DE) PD/T2-weighted MRI. FLAIR MRI scans were obtained from 17 clinically isolated syndromes patients on a 1.5T scanner. The method was based on a region growing approach initialized by manual identification of lesions. The stop condition was formulated combining intensity and edge detection constraints. High similarity with the manual segmentation (the gold standard) was found, as well as a low misclassification of lesion voxels. Operator time required for lesion segmentation was importantly reduced.
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