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Abstract:
Introduction: Multiple Sclerosis (MS) is an inflammatory, demyeli- nating autoimmune disorder affecting the central nervous system. Radiologically, detectable focal lesions, predominantly found in the myelin-rich white matter, are a common occurrence in the brains of MS patients 1 . These focal lesions are not uniformly distributed throughout the white matter; instead, they exhibit a spatial distribu- tion pattern characterized by periventricular accumulation 2 . To assess the lesion load in individual patients or to determine the presence of new lesions between two time points, automatic lesion detection algorithms are available, offering independence from investigator bias. The aim of this study is to obtain voxel-wise probabilities of lesion occurrence and overall brain lesion distribution by transform- ing the lesion masks and their corresponding anatomical images into the Montreal Neurological Institute (MNI) space.
