Left Ventricular

Left ventricular (LV) analysis is crucial for diagnosing and managing cardiovascular diseases, focusing on accurate segmentation and quantification of its structure and function from various imaging modalities like MRI and echocardiography. Current research heavily utilizes deep learning, particularly U-Net and its variants, along with graph neural networks and vision transformers, to automate this process, often incorporating self-supervised and weakly-supervised learning techniques to address data scarcity and variability. These advancements aim to improve the accuracy, robustness, and efficiency of LV assessment, ultimately leading to better patient care and more reliable clinical decision-making.