Myocardial Viability

Myocardial viability assessment focuses on determining the health of heart muscle tissue, crucial for diagnosing and treating conditions like myocardial infarction. Current research emphasizes improving the accuracy and efficiency of viability assessment using advanced image analysis techniques, particularly leveraging deep learning models like convolutional neural networks (CNNs) and variational autoencoders (VAEs) to analyze data from multiple cardiac magnetic resonance (CMR) sequences. These advancements aim to enhance the precision of diagnosis, personalize treatment planning, and ultimately improve patient outcomes by providing more reliable information about the extent and nature of heart damage.