通过经验丰富的操作人员的深度学习进行实时指导,以提高心声回声采集的标准化
Sigbjorn Sabo1,2, David Pasdeloup1, Hakon Neergaard Pettersen1,3
1Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, PO Box 8905, 7491 Trondheim, Norway.
European heart journal. Imaging methods and practice
|July 24, 2024
概括
深度学习 (DL) 指导改善了经验丰富的超声波专家对心声回声图的标准化. 这项技术提高了图像采集质量,可能减少心脏评估中操作员间的变化.
科学领域:
- 心脏病学 心脏病学
- 医疗成像医学成像
- 人工智能的人工智能
背景情况:
- 心声图的标准化对于准确的心脏评估至关重要.
- 运营商间的变化可能来自不一致的图像采集.
- 深度学习 (DL) 为改善标准化提供了潜在的解决方案.
研究的目的:
- 评估实时深度学习 (DL) 指导是否可以增强尖端心声录像记录的标准化.
- 评估DL对心声回声学中操作者间变异性的影响.
主要方法:
- 88名鼻节律患者接受了三次心声回声检查.
- 超声波仪进行了两个检查:一个没有DL指导 (期1) 和一个实时DL指导 (期2).
- 图像标准化被人类专家和DL算法回顾评估,重点是旋转和倾斜.
主要成果:
- 使用DL指导的超声波仪与没有指导的超声波仪相比 (P ≤ 0.05) 实现了显著更多的标准化顶峰记录.
- 人类专家和DL的评估都显示DL指导的标准化得到了改善.
- 特定的视图,如顶峰双腔和顶峰长轴旋转,以及顶峰双腔倾斜,显示出显著的改进.
结论:
- 实时深度学习 (DL) 指导有效地提高了经验丰富的超声波专家对心声回声采集的标准化.
- 需要进一步的研究来探索DL对测量变量的影响及其对经验较少的操作员的有用性.
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