A large public dataset of annotated clinical MRIs and metadata of patients with acute stroke.

ABSTRACT: To extract meaningful and reproducible models of brain function from stroke images, for both clinical and research proposes, is a daunting task severely hindered by the great variability of lesion frequency and patterns. Large datasets are therefore imperative, as well as fully automated image post-processing tools to analyze them. The development of such tools, particularly with artificial intelligence, is highly dependent on the availability of large datasets to model training and testing. We present a public dataset of 2,888 multimodal clinical MRIs of patients with acute and early subacute stroke, with manual lesion segmentation, and metadata. The dataset provides high quality, large scale, human-supervised knowledge to feed artificial intelligence models and enable further development

SUBMITTER: Liu CF 

PROVIDER: S-EPMC10444746 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature