Snake segmentation of multiple sclerosis lesions for assisted diagnosis by cluster analysis-based techniques

Magnetic Resonance Imaging (MRI), allowing in-vivo detection of lesions, is today a crucial tool for diagnosis of Multiple Sclerosis (MS). Although the detection of lesions are not sufficient for a diagnosis of MS because of sirnilarity with patterns detected in other neurological diseases, taking into account different radiological informations, MRI findings can often yield a high degree of confidence. We used a snake based procedure for segmentation of lesion then proposing a method based on Cluster Analysis to support clinicians in the diagnosis of MS. By identifying a minimum set of significant descriptors, our algorithm can help neurologist and neuroimaging expert to distinguish MS plaques from other kinds of lesions.