使用机器学习和深度学习检测和定量冠状动脉的狭窄
Xinhong Zhang1, Boyan Zhang1, Fan Zhang2
1School of Software, Henan University, Kaifeng, China.
Angiology
|July 3, 2023
概括
人工智能 (AI) 算法,包括机器学习和深度学习,正在推进使用计算机断层扫描血管学 (CTA) 的冠状动脉狭窄检测和量化. 由于对这些人工智能方法需要大量的注释数据集,仍然存在挑战.
科学领域:
- 心脏病学 心脏病学
- 放射学 放射学是一门学科.
- 人工智能的人工智能
背景情况:
- 冠状动脉疾病是全球死亡的主要原因之一.
- 准确检测和定量冠状动脉狭窄症对于患者管理至关重要.
- 计算机断层扫描血管造影 (CTA) 是评估冠状动脉的关键成像方式.
研究的目的:
- 审查人工智能 (AI) 算法的应用,用于使用CTA检测和量化冠状动脉狭窄.
- 总结最近的进展,并讨论人工智能驱动的冠状动脉狭窄分析的未来趋势.
- 为研究人员提供不同人工智能方法的比较概述.
主要方法:
- 关于人工智能在冠状动脉狭窄检测和量化中的应用现有文献的综述.
- 专注于机器学习和深度学习技术.
- 分析所涉及的步骤:血管中心轴提取,细分,狭窄检测和量化.
主要成果:
- 人工智能,特别是机器学习和深度学习,在自动化冠状动脉狭窄检测和量化方面显示出重大前景.
- 这些人工智能技术越来越多地用于医学图像细分和狭窄检测.
- 该审查强调了各种人工智能方法的进展和比较优势/缺点.
结论:
- 人工智能算法准备加强冠状动脉狭窄检测和量化的自动化.
- 当前人工智能方法的一个主要挑战是需要广泛的,专业注释的数据集.
- 需要进一步的研究来克服数据注释的局限性,并优化AI技术在这个领域.
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