Carotid Ultrasound

Carotid ultrasound imaging is used to assess carotid artery health, primarily focusing on detecting and characterizing plaque buildup, a major risk factor for stroke. Current research emphasizes improving image quality and analysis through deep learning techniques, including convolutional neural networks (CNNs), generative adversarial networks (GANs), and transformer architectures, to automate tasks like plaque segmentation and stenosis grading from both still images and video sequences. These advancements aim to improve diagnostic accuracy, reduce variability between clinicians, and ultimately enhance the efficiency and effectiveness of cardiovascular risk assessment.