Abstract #2666

AI-based Computer-Aided System for Cardiovascular Disease Evaluation (AI-CASCADE) for carotid tissue quantification

Yin Guo¹, Li Chen², Dongxiang Xu³, Rui Li⁴, Xihai Zhao⁴, Thomas S. Hatsukami⁵, and Chun Yuan^1,3

¹Bioengineering, University of Washington, Seattle, WA, United States, ²Electrical Engineering, University of Washington, Seattle, WA, United States, ³Radiology, University of Washington, Seattle, WA, United States, ⁴Biomedical Engineering, Tsinghua University, Beijing, China, ⁵Surgery, University of Washington, Seattle, WA, United States

The tissue composition of carotid atherosclerotic plaques is crucial for cardiovascular risk assessment and can be quantified with high-resolution multi-contrast MRI by expert reviewers. The purpose of this work is to develop AI-CASCADE, a fully automated solution for quantitative analysis of carotid MRI, including artery localization, vessel wall segmentation, artery registration and plaque component segmentation. Results in our preliminary study show that AI-CASCADE achieves good agreements with manual results and has great potential as an efficient and reliable clinical tool.

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