DOI: 10.3886/icpsr36684.v5
title: The Anatomical Tracings of Lesions after Stroke (ATLAS) Dataset - Release 2.0, 2021
title: Version 5

description: <strong>
To access this data collection, please click on the Restricted Data button above. You will need to download and complete the data use agreement and then email it to icpsr-addep@umich.edu. The instructions are in the form.
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The Anatomical Tracings of Lesions After Stroke (ATLAS) Dataset - Release 2.0 is an open-source data collection consisting a total of 955 T1-weighted MRIs (Magnetic Resonance Imaging) with manually segmented diverse lesions and metadata. ATLAS v2.0 has been split into a public release of 655 T1w MRIs and lesion masks and a hidden test dataset of 300 T1w MRIs. For the hidden dataset, only the T1s MRIs are available. The accompanying manually segmented lesion masks will be made available only for testing algorithm performance in lesion segmentation challenges and competitions. The goal of ATLAS is to provide the research community with a standardized training and testing dataset for lesion segmentation algorithms on T1-weighted MRIs.


From 33 cohorts worldwide, 955 MRI images were collected from research groups in the ENIGMA Stroke Recovery Working Group consortium. Images consisted of T1-weighted anatomical MRIs of individuals after stroke. For each MRI, brain lesions were identified and masks were manually drawn on each individual brain in native space using ITK-SNAP (version 3.8.0). After tracing, researchers reviewed and edited lesion masks as necessary using a standardized quality control protocol. In a subset of the data, lesion masks were received from the originating site and edited and checked for quality by the team. All team members received lesion-tracing training and followed a standard operating protocol for tracing lesions to ensure inter-rater reliability on all manually traced masks. All lesion masks were checked twice for quality by trained team members. During the quality control process, researchers ensured that the boundaries of the lesion segmentation were accurate and that all identifiable lesions in the brain were traced. All subject files have undergone a lesion tracing and preprocessing pipeline and are named and stored in accordance with the Brain Imaging Data Structure (BIDS) This dataset is provided in both native subject space and normalized to a standard template (the MNI-152 template).
description: Research groups in the ENIGMA Stroke Recovery Working Group consortium collected 955 MRI images from 33 cohorts worldwide. Images consisted of T1-weighted anatomical MRIs of individuals after stroke. For each MRI, brain lesions were identified and masks were manually drawn on each individual brain in native space using ITK-SNAP (version 3.8.0). After tracing, researchers reviewed and edited lesion masks as necessary using a standardized quality control protocol. In a subset of the data, lesion masks were received from the originating site and edited and checked for quality by the team. All team members received lesion-tracing training and followed a standard operating protocol for tracing lesions to ensure inter-rater reliability on all manually traced masks. All lesion masks were checked twice for quality by trained team members. During the quality control process, researchers ensured that the boundaries of the lesion segmentation were accurate and that all identifiable lesions in the brain were traced. The data collection is provided in both native subject space and normalized to a standard template (the MNI-152 template).
description: None
description: Convenience samples at 33 different locations worldwide.
This is a harmonized sample of retrospective MRI data collected from 20 different international research studies.
description: Datasets: 
DS1: The Anatomical Tracings of Lesions after Stroke (ATLAS) Dataset - Release 2.0, 2021
description: MRIs of individuals from around the world who have suffered a stroke. Smallest Geographic Unit: None
description: mixed mode
Before analyzing the data, users are encouraged to review the README file and the PI Documentation file, both available for download from the study home page. Please contact ADDEP staff at icpsr-addep@umich.edu for further information about the data.


Users are also encouraged to refer to the bioRxiv article for any additional information about the study.
In the previous release, ATLAS v1.2, lesions were segmented using the NITRC open source software MRIcron which can be downloaded from the NITRC website. Users can also quickly and easily view the brains on BrainBox, an open-source Web application to collaboratively annotate and segment neuroimaging data available online. For additional quick quantification, a small toolbox was created. It is called SRQL (Semi-automated Robust Quantification of Lesions), which includes three features: it uses a semi-automated white matter intensity correction, outputs a report of descriptive statistics on lesions, and gives users the option to perform analyses in native or standard space. Finally, any issues or feedback can be submitted on the ATLAS GitHub 'issues' page, on which any updates, software, and additional releases will also be announced.The Pipeline for Analyzing Lesions After Stroke (PALS) open-source software has been updated, which allows users to easily calculate lesion volume, evaluate lesion overlap with brain regions of interest, and create lesion overlap images.