Myocardial Strain

Myocardial strain analysis quantifies the heart muscle's deformation during contraction and relaxation, providing crucial insights into cardiac function and disease. Current research heavily utilizes deep learning, employing convolutional neural networks and generative models like variational autoencoders, often incorporating advanced image registration techniques to improve accuracy and address challenges like motion estimation in regions with subtle changes. These advancements aim to enhance the precision and efficiency of strain analysis from standard cardiac imaging, leading to improved diagnosis and monitoring of cardiovascular diseases. The ultimate goal is to translate these improvements into more accurate and readily available clinical tools for assessing cardiac health.