Ricerc@Sapienza

Understanding the correlation and causal relationship between cardiovascular diseases and the heart shape is of utmost importance to improve diagnosis methodologies.
The MRI images are a common heart diagnostic tool that allow visualizing slices of the heart at different spatial levels, temporal steps and heart orientations. Several methods exist to reconstruct a 3D model of the heart for each time step yielding a 4D reconstruction, much less explored is the automatic discovery of correlations and causality relationships between geometric features of the reconstructed shape and cardiovascular diseases. This project aims to form a bridge between cutting-edge techniques in deep learning, geometric processing and heart imaging to improve the current diagnostic tools. An ongoing collaboration with the radiology team from the department of experimental medicine in the Umberto I hospital will provide domain expertise and MRI scans of at least 100 patients with and without ventricular segmentations.