A fully automated pipeline for brain structure segmentation in multiple sclerosis.

ABSTRACT: Accurate volume measurements of the brain structures are important for treatment evaluation and disease follow-up in multiple sclerosis (MS) patients. With the aim of obtaining reproducible measurements and avoiding the intra-/inter-rater variability that manual delineations introduce, several automated brain structure segmentation strategies have been proposed in recent years. However, most of these strategies tend to be affected by the abnormal MS lesion intensities, which corrupt the structure segmentation result. To address this problem, we recently reformulated two label fusion strategies of the state of the art, improving their segmentation performance on the lesion areas. Here, we integrate these reformulated strategies in a completely automated pipeline that includes pre-processing

SUBMITTER: Gonzalez-Villa S 

PROVIDER: S-EPMC7322098 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature