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ISLES 2022: A multi-center magnetic resonance imaging stroke lesion segmentation dataset.

Authors :
Hernandez Petzsche MR
de la Rosa E
Hanning U
Wiest R
Valenzuela W
Reyes M
Meyer M
Liew SL
Kofler F
Ezhov I
Robben D
Hutton A
Friedrich T
Zarth T
Bürkle J
Baran TA
Menze B
Broocks G
Meyer L
Zimmer C
Boeckh-Behrens T
Berndt M
Ikenberg B
Wiestler B
Kirschke JS
Source :
Scientific data [Sci Data] 2022 Dec 10; Vol. 9 (1), pp. 762. Date of Electronic Publication: 2022 Dec 10.
Publication Year :
2022

Abstract

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.<br /> (© 2022. The Author(s).)

Details

Language :
English
ISSN :
2052-4463
Volume :
9
Issue :
1
Database :
MEDLINE
Journal :
Scientific data
Publication Type :
Academic Journal
Accession number :
36496501
Full Text :
https://doi.org/10.1038/s41597-022-01875-5