  Carotid artery plaques can cause arterial vascular diseases such as stroke
and myocardial infarction, posing a severe threat to human life. However, the
current clinical examination mainly relies on a direct assessment by physicians
of patients' clinical indicators and medical images, lacking an integrated
visualization tool for analyzing the influencing factors and composition of
carotid artery plaques. We have designed an intelligent carotid artery plaque
visual analysis system for vascular surgery experts to comprehensively analyze
the clinical physiological and imaging indicators of carotid artery diseases.
The system mainly includes two functions: First, it displays the correlation
between carotid artery plaque and various factors through a series of
information visualization methods and integrates the analysis of patient
physiological indicator data. Second, it enhances the interface guidance
analysis of the inherent correlation between the components of carotid artery
plaque through machine learning and displays the spatial distribution of the
plaque on medical images. Additionally, we conducted two case studies on
carotid artery plaques using real data obtained from a hospital, and the
results indicate that our designed carotid analysis system can effectively
provide clinical diagnosis and treatment guidance for vascular surgeons.
