A comprehensive approach to the segmentation of multichannel three-dimensional MR brain images in multiple sclerosis.

ABSTRACT: Accurate classification and quantification of brain tissues is important for monitoring disease progression, measurement of atrophy, and correlating magnetic resonance (MR) measures with clinical disability. Classification of MR brain images in the presence of lesions, such as multiple sclerosis (MS), is particularly challenging. Images obtained with lower resolution often suffer from partial volume averaging leading to false classifications. While partial volume averaging can be reduced by acquiring volumetric images at high resolution, image segmentation and quantification can be technically challenging. In this study, we integrated the brain anatomical knowledge with non-parametric and parametric statistical classifiers for automatically classifying tissues and lesions on high resolutio

SUBMITTER: Datta S 

PROVIDER: S-EPMC3777770 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature