A large public dataset of annotated clinical MRIs and metadata of patients with acute stroke.


Journal

Scientific data
ISSN: 2052-4463
Titre abrégé: Sci Data
Pays: England
ID NLM: 101640192

Informations de publication

Date de publication:
22 08 2023
Historique:
received: 31 01 2023
accepted: 09 08 2023
medline: 24 8 2023
pubmed: 23 8 2023
entrez: 22 8 2023
Statut: epublish

Résumé

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.

Identifiants

pubmed: 37607929
doi: 10.1038/s41597-023-02457-9
pii: 10.1038/s41597-023-02457-9
pmc: PMC10444746
doi:

Types de publication

Dataset Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

548

Subventions

Organisme : NIBIB NIH HHS
ID : P41 EB031771
Pays : United States
Organisme : NIDCD NIH HHS
ID : P50 DC014664
Pays : United States
Organisme : NIDCD NIH HHS
ID : R01 DC005375
Pays : United States
Organisme : NIDCD NIH HHS
ID : R01 DC015466
Pays : United States

Informations de copyright

© 2023. Springer Nature Limited.

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Auteurs

Chin-Fu Liu (CF)

Center for Imaging Science, Johns Hopkins University, Baltimore, MD, USA.
Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.

Richard Leigh (R)

Department of Neurology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA.

Brenda Johnson (B)

Department of Neurology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA.

Victor Urrutia (V)

Department of Neurology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA.

Johnny Hsu (J)

Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA.

Xin Xu (X)

Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA.

Xin Li (X)

Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA.

Susumu Mori (S)

Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA.

Argye E Hillis (AE)

Department of Neurology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA.
Department of Physical Medicine & Rehabilitation, and Department of Cognitive Science, Johns Hopkins University, Baltimore, MD, USA.

Andreia V Faria (AV)

Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA. afaria1@jhmi.edu.

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