A comparison of automated lesion segmentation approaches for chronic stroke T1-weighted MRI data.

ABSTRACT: Accurate stroke lesion segmentation is a critical step in the neuroimaging processing pipeline for assessing the relationship between poststroke brain structure, function, and behavior. Many multimodal segmentation algorithms have been developed for acute stroke neuroimaging, yet few algorithms are effective with only a single T1-weighted (T1w) anatomical MRI. This is a critical gap because multimodal MRI is not commonly available due to time and cost constraints in the stroke rehabilitation setting. Although several attempts to automate the segmentation of chronic lesions on single-channel T1w MRI have been made, these approaches have not been systematically evaluated on a large dataset. We performed an exhaustive review of the literature and identified one semiautomated and three fully a

SUBMITTER: Ito KL 

PROVIDER: S-EPMC6851560 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature