人工智能诊断和热图剂使用3D电影心声
Defu Zhang1,2, Miaoru Yu1,2, Xueyuan Lin1,2
1Department of Ultrasound, The Second Clinical Medical College, Jinan University (Shenzhen People's Hospital), Shenzhen 518020, China.
iScience
|August 21, 2025
概括
这项研究引入了一种人工智能剂,用于使用心声影像数据诊断膜脱落 (MVP),达到高精度. 人工智能还可视化MVP, 帮助手术规划.
科学领域:
- 心脏病学
- 人工智能
- 医学成像
背景情况:
- 3D心声学可以提高对膜脱落 (MVP) 的检测.
- 目前的深度学习专注于用于心脏结构测量的voxel数据,而忽视用于MVP诊断的cine数据.
- 在使用电影数据的自动化MVP诊断和可视化中存在差距.
研究的目的:
- 使用电影数据开发人工智能 (AI) 代理用于MVP的自动诊断和热图可视化.
- 解决心脏成像当前深度学习方法的局限性.
- 提供一个准确的MVP评估和手术计划的工具.
主要方法:
- 从151名受试者中使用了481个心脏周期 (8422) 进行训练和验证.
- 开发了一种专注于从电影数据中诊断和生成热图的AI代理.
- 使用AUC,精度和F1得分评估诊断性能;使用Dice和IoU指标评估热图质量.
主要成果:
- 在患者水平上,AI药物实现了高诊断性能:AUC为99. 54%,准确率为95. 08%,F1得分为94. 12%.
- MVP的热图生成显示了Dice系数为70.35%和IOU为56.39%.
- 人工智能的热图性能大约超过了高级和初级医生的5%.
结论:
- 开发的人工智能药物显示出使用心声影像数据进行准确和标准化的MVP诊断的巨大潜力.
- 人工智能的直观热图可视化有助于了解的严重程度和位置.
- 这项技术可以支持MVP手术管理和治疗计划的临床决策.
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