Automatic segmentation of white matter lesion MRI brain

Abstract

A method to automatically segment cerebrospinal fluid, gray matter, white matter and white matter lesions is presented. The method uses magnetic resonance brain images from proton density. T1-weighted and fluid-attenuated inversion recovery sequences. The method is based on an automatically trained k-nearest neighbour classifier extended with an additional step for the segmentation of white matter lesions. On six datasets, segmentations are quantitatively compared with manual segmentations, which have been carried out by two expert observers. For the tissues, similarity indices between method and observers approximate those between manual segmentations. Reasonably good lesion segmentation results are obtained compared to interobserver variability.