Cardiac MRI (CMRI) is crucial for assessing cardiovascular structure and function, yet manual analysis is time-consuming and subjective. This paper introduces CMRI Insight, an open-source, Python-based GUI tool designed for automated cardiac segmentation and motion tracking like CardioTrackNet in CMRI. Leveraging deep learning models like CardSegNet and MECardNet, it enables accurate delineation of the left ventricle, right ventricle, and myocardium with mean Dice scores of 95.8% for the left ventricle, 94.2% for the right ventricle, and 95.0% for the myocardium. The tool offers 3D mesh reconstruction, strain analysis, bull’s-eye visualization, and support for custom models. CMRI Insight enhances efficiency and reproducibility in cardiac imaging research and clinical evaluation, providing a user-friendly platform for comprehensive CMRI analysis.
Aghapanah et al. (Fri,) studied this question.