ISLES'24 : a real-world longitudinal multimodal stroke dataset

This multi-center dataset consists of 149 acute ischemic stroke cases, representing the training set of the ISLES'24 challenge. All data are provided in NIfTI format (.nii.gz) and organized according to the BIDS standard. For each case, the following data are included: - Admission imaging: non-contrast CT (NCCT), CT angiography (CTA), 4D CT perfusion (CTP) time series, and perfusion maps (Tmax, CBF, CBV, MTT). - Follow-up imaging: post-treatment MRI (DWI and ADC). - Clinical data: demographics, patient history, admission NIHSS, 3‑month functional outcome (mRS), etc. - Annotations: binary infarct masks derived from follow-up MRI (lesion-msk.nii.gz), large vessel occlusion binary masks derived from CTA (lvo-msk.nii.gz), and the multi-labeled Circle of Willis anatomy generated with an automatic algorithm over CTA (cow-msk.nii.gz) This dataset combines multimodal imaging, longitudinal follow-up, and structured clinical variables to support benchmarking of stroke infarct prediction methods.

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Publication Details

Journal
Zürcher Hochschule für Angewandte Wissenschaften digital collection (Zurich University of Applied Sciences)
Published
2025-11-20
DOI
https://doi.org/10.5281/zenodo.17652035
Primary Topic
Acute Ischemic Stroke Management
Type
article
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article

ISLES'24 : a real-world longitudinal multimodal stroke dataset

Moritz Roman Hernández Petzsche, Houjing Huang, The Anh Baran, Joaquin Oscar Seia et al.
Zürcher Hochschule für Angewandte Wissenschaften digital collection (Zurich University of Applied Sciences)
Acute Ischemic Stroke Management
article

ISLES'24 : a real-world longitudinal multimodal stroke dataset

Moritz Roman Hernández Petzsche, Houjing Huang, The Anh Baran, Joaquin Oscar Seia, Evamaria Olga Riedel, Hakim Baazaoui, David Robben, Mauricio Reyes, Tobias Boeckh-Behrens, Benedikt Wiestler, Kaiyuan Yang, Claus Zimmer, Bjoern Menze, Susanne Wegener, Maria Berndt, Daniel Rueckert, Roland Wiest
article en

Abstract

This multi-center dataset consists of 149 acute ischemic stroke cases, representing the training set of the ISLES'24 challenge. All data are provided in NIfTI format (.nii.gz) and organized according to the BIDS standard. For each case, the following data are included: - Admission imaging: non-contrast CT (NCCT), CT angiography (CTA), 4D CT perfusion (CTP) time series, and perfusion maps (Tmax, CBF, CBV, MTT). - Follow-up imaging: post-treatment MRI (DWI and ADC). - Clinical data: demographics, patient history, admission NIHSS, 3‑month functional outcome (mRS), etc. - Annotations: binary infarct masks derived from follow-up MRI (lesion-msk.nii.gz), large vessel occlusion binary masks derived from CTA (lvo-msk.nii.gz), and the multi-labeled Circle of Willis anatomy generated with an automatic algorithm over CTA (cow-msk.nii.gz) This dataset combines multimodal imaging, longitudinal follow-up, and structured clinical variables to support benchmarking of stroke infarct prediction methods.

Zürcher Hochschule für Angewandte Wissenschaften digital collection (Zurich University of Applied Sciences)
Good health and well-being
Openalex Percentile: Top 26%
Acute Ischemic Stroke Management
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