Artificial Intelligence in Image-based Cardiovascular Disease Analysis: A Comprehensive Survey and Future Outlook
arxiv(2024)
摘要
Recent advancements in Artificial Intelligence (AI) have significantly
influenced the field of Cardiovascular Disease (CVD) analysis, particularly in
image-based diagnostics. Our paper presents an extensive review of AI
applications in image-based CVD analysis, offering insights into its current
state and future potential. We systematically categorize the literature based
on the primary anatomical structures related to CVD, dividing them into
non-vessel structures (such as ventricles and atria) and vessel structures
(including the aorta and coronary arteries). This categorization provides a
structured approach to explore various imaging modalities like Magnetic
Resonance Imaging (MRI), which are commonly used in CVD research. Our review
encompasses these modalities, giving a broad perspective on the diverse imaging
techniques integrated with AI for CVD analysis. Additionally, we compile a list
of publicly accessible cardiac image datasets and code repositories, intending
to support research reproducibility and facilitate data and algorithm sharing
within the community. We conclude with an examination of the challenges and
limitations inherent in current AI-based CVD analysis methods and suggest
directions for future research to overcome these hurdles.
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