Arterial Wall

Arterial wall research focuses on understanding its structure and function, particularly concerning atherosclerosis and cardiovascular disease. Current investigations utilize advanced imaging techniques (e.g., IVOCT, MRI, CCTA) coupled with deep learning models (like U-Nets, cGANs, and mesh neural networks) to improve the accuracy and efficiency of plaque detection, segmentation, and stress-strain mapping. These efforts aim to enhance cardiovascular risk assessment and guide personalized treatment strategies, such as targeted drug delivery systems, by providing more precise and readily available information about arterial wall conditions. The ultimate goal is to improve patient outcomes through earlier diagnosis and more effective interventions.