An Explainable Machine Learning Approach Reveals Prognostic Significance of Right Ventricular Dysfunction in Nonischemic Cardiomyopathy

Abstract

Myocardial perfusion assessment using cardiac MRI allows non-invasive asseessmnet of myocardial ischmia. In myocardial perfusion sequence, imaging is collected after a saturation pulse. An alternative approach based on stready-state imaging with radial sampling has been recently proposed. However, image reconstruction using compressed sensing in steady-state myocardial perfusion remains long and clinically not feasible. In this study, we sought to develop a deep learning-based image recosntruciton platform for myocardial perfusion imaging.

Publication
In International Society for Magnetic Resonance
Salah Assana
Salah Assana
Research Assistant

My research interests include signal processing, cardiology and artificial intelligence.