A dataset derived from cardiac magnetic resonance imaging (CMRI) stands as a valuable asset, offering non-invasive insights into cardiac structure and function pivotal for the diagnosis, treatment, and research of cardiac conditions. In 2023, the Cardiovascular Disease Research Institute (CVDRI) undertook Iran's most comprehensive cardiac MRI study, centring on left ventricular (LV) and myocardial (Myo) cross-sectional assessments. This study included both short-axis and long-axis MRI images to create three-dimensional representations. The RAJAIE CMRI dataset initially comprised 22 individuals aged between 35 and 75. Presently, it has expanded to encompass 50 cases recruited from 2020 to 2024, categorized into four groups: Heart failure with infarction (HF-I), Heart failure without infarction (HF), LV hypertrophy (HYP), and Healthy (N) individuals with an ejection fraction exceeding 55%. The integration of diverse cardiac imaging perspectives constitutes a substantial asset for research pertaining to health-related matters. This paper introduces an innovative methodology aimed at enhancing image storage and achieving 4D cardiac image visualization (3D in frame sequences), thus contributing to the advancement of cardiac imaging and research capabilities, and the newest codes are available on GitHub
for download data of CMRI click hear
Please reference the following paper if you would like to use any part of this dataset or method:
[3] H. Aghapanah, R. Rasti, and S. Kermani, “CardioTrackNet: A Hybrid Active Mesh and PWC Model for Enhanced Cardiac MRI Motion Analysis and Visualization BT - Proceedings of the Iranian Conference on Biomedical Engineering (ICBME 2024),” 2024.