An Integrated Visual Analytics System for Studying Clinical Carotid Artery Plaques

August 09, 2023 Β· Declared Dead Β· πŸ› Journal of Vision

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Authors Chaoqing Xu, Zhentao Zheng, Yiting Fu, Baofeng Chang, Legao Chen, Minghui Wu, Mingli Song, Jinsong Jiang arXiv ID 2308.06285 Category cs.HC: Human-Computer Interaction Cross-listed eess.IV Citations 1 Venue Journal of Vision Last Checked 4 months ago
Abstract
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.
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