ArticleScientific data2023
A large public dataset of annotated clinical MRIs and metadata of patients with acute stroke.
Article in Scientific data, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Learning neuroimaging models from health system-scale data.Nature biomedical engineering · 2026Article
- Deep learning in acute ischemic stroke imaging: a systematic review of CT- and MRI-based segmentation, triage, and prognostic modeling.Neuroradiology · 2026Review
- Multi-dimensional MRI representation and privileged learning approaches to functional outcome prediction for ischemic stroke patients.NPJ digital medicine · 2026Article
- AI post-intervention operational and functional outcomes prediction in ischemic stroke patients using MRIs.BMC medical imaging · 2025Article
- DeepISLES: a clinically validated ischemic stroke segmentation model from the ISLES'22 challenge.Nature communications · 2025Article
- Learning neuroimaging models from health system-scale data.Research square · 2025Article
- From MRIcro to MRIcron: The evolution of neuroimaging visualization tools.Neuropsychologia · 2025Article
- Heterogeneous transfer learning model for improving the classification performance of fNIRS signals in motor imagery among cross-subject stroke patients.Frontiers in human neuroscience · 2025Article
- MRAnnotator: multi-anatomy and many-sequence MRI segmentation of 44 structures.Radiology advances · 2025Article
- Technological Advancements in Augmented, Mixed, and Virtual Reality Technologies for Surgery: A Systematic Review.Cureus · 2024Review
- APIS: a paired CT-MRI dataset for ischemic stroke segmentation - methods and challenges.Scientific reports · 2024Article
- The stroke outcome optimization project: Acute ischemic strokes from a comprehensive stroke center.Scientific data · 2024Article
- The Multicentre Acute ischemic stroke imaGIng and Clinical data (MAGIC) repository: rationale and blueprint.Frontiers in neuroinformatics · 2024Article
- Automatic comprehensive radiological reports for clinical acute stroke MRIs.Communications medicine · 2023Article
- Association of inferior division MCA stroke location with populations with atrial fibrillation incidence.Heliyon · 2023Article
- Automatic comprehensive aspects reports in clinical acute stroke MRIs.Scientific reports · 2023Article
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Authors and funding
10 authors.
Funding
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 of tools to automate several tasks that currently rely on human labor, such as lesion segmentation, labeling, calculation of disease-relevant scores, and lesion-based studies relating function to frequency lesion maps.
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