Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
60
datasets available to search
ShareScore release 0.9.0
Dataset results
60 results for “Cardiovascular magnetic resonance”
Cardiovascular Magnetic Resonance Prognosticators in Pediatric Oncology Patients With Sepsis
ClinicalTrials.gov study NCT05930418. IPD Sharing: NO. Countries: 1. Publications: 0.
Clinical Significance of Subclinical Myocardial Involvement in Recovered COVID-19 Patients Using Cardiovascular Magnetic Resonance (R-COVID-CMR)
ClinicalTrials.gov study NCT04864899. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Impact of Ranolazine on Myocardial Ischemia Detected by High-Field 3T Cardiovascular Magnetic Resonance (CMR) Imaging and P-31 Spectroscopy
ClinicalTrials.gov study NCT01804543. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Assessment of Cardiac Function Using Combined Cardiovascular Magnetic Resonance and Cardiopulmonary Exercise Testing (CMR-CPET)
ClinicalTrials.gov study NCT04729777. IPD Sharing: YES. Countries: 1. Publications: 0.
Latin American Multicenter Cardiovascular Magnetic Resonance Reference Study
ClinicalTrials.gov study NCT01030549. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Using Cardiovascular Magnetic Resonance Tissue Characterisation and Wearable Technology to PREDICT Clinical Outcomes, Response to Therapy and Arrhythmias in Hospitalised Heart Failure Patients
ClinicalTrials.gov study NCT03689426. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
3D Cine Cardiovascular Magnetic Resonance
ClinicalTrials.gov study NCT03583775. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Athlete's Heart or Arrhythmogenic Right Ventricular Cardiomyopathy: Contribution of Exercise Cardiovascular Magnetic Resonance (CMR)
ClinicalTrials.gov study NCT05024708. IPD Sharing: NO. Countries: 1. Publications: 0.
The Acute Cardiovascular Effects of Marathon Running Using Magnetic Resonance Imaging
ClinicalTrials.gov study NCT00752752. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Stress Cardiac Magnetic Resonance of Asymptomatic Type 2 Diabetics with Cardiovascular High Risk to Measure Empagliflozin Impact on Myocardial Blood Flow (CATCH-EM)
ClinicalTrials.gov study NCT04541797. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Study of Polyglycan Superparamagnetic Ferric Oxide Injection on Cardiovascular Magnetic Resonance Imaging
ClinicalTrials.gov study NCT05687864. IPD Sharing: NO. Countries: 1. Publications: 0.
Automated Reports Generation of Cardiovascular Magnetic Resonance Imaging
ClinicalTrials.gov study NCT07340762. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Haemodynamics and Function of the Atria in Congenital Heart Disease by Cardiovascular Magnetic Resonance
ClinicalTrials.gov study NCT02161471. IPD Sharing: Not stated. Countries: 1. Publications: 0.
The Role of Cardiovascular Magnetic Resonance in Patients With Non-ST- Elevation- Myocardial Infarction
ClinicalTrials.gov study NCT05751057. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
A 10-Minute Cardiovascular Magnetic Resonance Protocol for Cardiac Disease
ClinicalTrials.gov study NCT04464655. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Cardiovascular Magnetic Resonance in Adults With SysTemic Right Ventricle (STAR)
ClinicalTrials.gov study NCT05690854. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Cardiovascular Contrast-enhanced Magnetic Resonance Imaging Using Polysaccharide Superparamagnetic Iron Oxide Injection in Diabetic Patients
ClinicalTrials.gov study NCT06051565. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Development of New Software Capabilities for Use With Cardiovascular Magnetic Resonance Imaging
ClinicalTrials.gov study NCT00593541. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Cardiovascular Magnetic Resonance GUIDEd Insertion of Implantable Cardiac Defibrillator in Dilated CardioMyopathy
ClinicalTrials.gov study NCT03993730. IPD Sharing: NO. Countries: 0. Publications: 0.
Dataset related to the article "Cardiovascular magnetic resonance images with susceptibility artifacts: artificial intelligence with spatial-attention for ventricular volumes and mass assessment"
<p>This record contains raw data related to the article "Cardiovascular magnetic resonance images with susceptibility artifacts: artificial intelligence with spatial-attention for ventricular volumes and mass assessment"</p> <p>Abstract</p> <p>Background</p> <p>Segmentation of cardiovascular magnetic resonance (CMR) images is an essential step for evaluating dimensional and functional ventricular parameters as ejection fraction (EF) but may be limited by artifacts, which represent the major challenge to automatically derive clinical information. The aim of this study is to investigate the accuracy of a deep learning (DL) approach for automatic segmentation of cardiac structures from CMR images characterized by magnetic susceptibility artifact in patient with cardiac implanted electronic devices (CIED).</p> <p>Methods</p> <p>In this retrospective study, 230 patients (100 with CIED) who underwent clinically indicated CMR were used to developed and test a DL model. A novel convolutional neural network was proposed to extract the left ventricle (LV) and right (RV) ventricle endocardium and LV epicardium. In order to perform a successful segmentation, it is important the network learns to identify salient image regions even during local magnetic field inhomogeneities. The proposed network takes advantage from a spatial attention module to selectively process the most relevant information and focus on the structures of interest. To improve segmentation, especially for images with artifacts, multiple loss functions were minimized in unison. Segmentation results were assessed against manual tracings and commercial CMR analysis software cvi<sup>42</sup>(Circle Cardiovascular Imaging, Calgary, Alberta, Canada). An external dataset of 56 patients with CIED was used to assess model generalizability.</p> <p>Results</p> <p>In the internal datasets, on image with artifacts, the median Dice coefficients for end-diastolic LV cavity, LV myocardium and RV cavity, were 0.93, 0.77 and 0.87 and 0.91, 0.82, and 0.83 in end-systole, respectively. The proposed method reached higher segmentation accuracy than commercial software, with performance comparable to expert inter-observer variability (bias ± 95%LoA): LVEF 1 ± 8% vs 3 ± 9%, RVEF − 2 ± 15% vs 3 ± 21%. In the external cohort, EF well correlated with manual tracing (intraclass correlation coefficient: LVEF 0.98, RVEF 0.93). The automatic approach was significant faster than manual segmentation in providing cardiac parameters (approximately 1.5 s vs 450 s).</p> <p>Conclusions</p> <p>Experimental results show that the proposed method reached promising performance in cardiac segmentation from CMR images with susceptibility artifacts and alleviates time consuming expert physician contour segmentation.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.