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Dataset . 2022
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2022
License: CC BY
Data sources: ZENODO
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ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
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Open data repository, An et al., Deep learning-based automated lesion segmentation on mouse stroke magnetic resonance images

Authors: An, Jeehye; Wendt, Leo; Wiese, Georg; Herold, Tom; Rzepka, Norman; Mueller, Susanne; Koch, Stefan Paul; +3 Authors

Open data repository, An et al., Deep learning-based automated lesion segmentation on mouse stroke magnetic resonance images

Abstract

Open data repository of journal article "Deep learning-based automated lesion segmentation on mouse stroke magnetic resonance images" by Jeehye An et al. At time of publication of this dataset, the manuscript is still under revision. This dataset contains mouse T2 weighted MRI data, and manually and automated segmented ischemic stroke lesion masks for developing and evaluating a deep learning-based automated lesion segmentation. All files are in NIFTI format.

Keywords

MRI, stroke, mouse, lesion, deep learning, segmentation

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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