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ISLES 2022: A multi-center magnetic resonance imaging stroke lesion segmentation dataset.
Sci. Data 9:762 (2022)
Magnetic resonance imaging (MRI) is an important imaging modality in stroke. Computer based automated medical image processing is increasingly finding its way into clinical routine. The Ischemic Stroke Lesion Segmentation (ISLES) challenge is a continuous effort to develop and identify benchmark methods for acute and sub-acute ischemic stroke lesion segmentation. Here we introduce an expert-annotated, multicenter MRI dataset for segmentation of acute to subacute stroke lesions (https://doi.org/10.5281/zenodo.7153326). This dataset comprises 400 multi-vendor MRI cases with high variability in stroke lesion size, quantity and location. It is split into a training dataset of n = 250 and a test dataset of n = 150. All training data is publicly available. The test dataset will be used for model validation only and will not be released to the public. This dataset serves as the foundation of the ISLES 2022 challenge (https://www.isles-challenge.org/) with the goal of finding algorithmic methods to enable the development and benchmarking of automatic, robust and accurate segmentation methods for ischemic stroke.
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Publication type
Article: Journal article
Document type
Scientific Article
Keywords
Apparent Diffusion-coefficient; Acute Ischemic-stroke; Time-course; Infarct Volume; Final Infarct; Symptom Onset; Perfusion; Thrombectomy; Thrombolysis; Evolution
ISSN (print) / ISBN
2052-4463
e-ISSN
2052-4463
Journal
Scientific Data
Quellenangaben
Volume: 9,
Issue: 1,
Article Number: 762
Publisher
Nature Publishing Group
Publishing Place
London
Non-patent literature
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Reviewing status
Peer reviewed
Grants
Projekt DEAL