Fully Automated Myocardial Strain Estimation from Cardiovascular MRI–tagged Images Using a Deep Learning Framework in the UK Biobank is a dataset published in Radiology Cardiothoracic Imaging (2020). On theSindex it has a DataRank of 2.1, placing it in the top 10.1% of the data-sharing corpus. It has been cited 48 times, with 44 citing works in its 1-hop citation network.
Ranks in the top 10% for downstream scientific impact
Linked data & code
DataRank reads this dataset's downstream impact straight off the citation graph — no black box, no proprietary weighting. How is this computed?
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Base Score Contribution
0.584
From this paper's citation signal
Citation Network Contribution
1.5
From 39 citing papers with measurable signal
Ranked by each citer's contribution to N(p) — log1p(Cq) divided by its reference count — out of 44 citers.
British Heart Foundation
Grant: PG/14/89/31194
National Institutes of Health
Grant: 1R01HL121754
Health Research Council of New Zealand
Grant: 17/234
NIHR Barts Biomedical Research Centre and from the “SmartHeart” EPSRC
Grant: EP/P001009/1
SmartHeart: Next-generation cardiovascular healthcare via integrated image acquisition, reconstruction, analysis and learning
Wellcome Trust Research Training Fellowship
Grant: 203553/Z/Z
Medical Research Council
Grant: MR/L016311/1
MICA: Medical Bioinformatics: Data-Driven Discovery for Personalised Medicine
Medical Research Council
Grant: MC_QA137853
Wellcome Trust
Grant: 203553
Wellcome Trust
Grant: 203553/Z/16/Z
National Institute for Health Research (NIHR)
Grant: ACF-2016-19-001
NHLBI NIH HHS
Grant: R01 HL121754
National Institute for Health Research (NIHR)
Grant: CL-2019-19-003
Medical Research Council
Grant: MC_PC_17228
National Institutes of Health
Grant: 2R01HL121754-05
The Cardiac Atlas Project
NIHR Oxford Biomedical Research Centre
FWCI
4.13
Citation Percentile
1.0%
Citation Trend
Fields of Study
Keywords
Sustainable Development Goals
Additional file 2 of Fully-automated global and segmental strain analysis of DENSE cardiovascular magnetic resonance using deep learning for segmentation and phase unwrapping
Additional file 2 of Fully-automated global and segmental strain analysis of DENSE cardiovascular magnetic resonance using deep learning for segmentation and phase unwrapping
Additional file 1 of Fully-automated global and segmental strain analysis of DENSE cardiovascular magnetic resonance using deep learning for segmentation and phase unwrapping
Additional file 1 of Fully-automated global and segmental strain analysis of DENSE cardiovascular magnetic resonance using deep learning for segmentation and phase unwrapping
Fully Automated Myocardial Strain Estimation from CMR Tagged Images using a Deep Learning Framework in the UK Biobank