Probabilistic segmentation of brain white matter lesions using texture-based classification

Abstract

Lesions in brain white matter can cause significant functional deficits, and are often associated with neurological disease. The quantitative analysis of these lesions is typically performed manually by physicians on magnetic resonance images and represents a non-trivial, time-consuming and subjective task. The proposed method automatically segments white matter lesions using a probabilistic texture-based classification approach. It requires no parameters to be set, assumes nothing about lesion location, shape or size, and demonstrates better results (Dice coefficient of 0.84) when compared with other, similar published methods.