基于计算机视觉的自动化性能指标的评估,用于内镜结石手术
Jackson Cabo1,2, Daiwei Lu3, Chase Floyd4
1Department of Urology, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Journal of endourology
|July 2, 2025
概括
计算机视觉模型可以客观地评估内镜结石治疗中的手术技巧. 来自视频的自动化绩效指标 (APM) 区分专家和学员的绩效,有助于技能评估.
科学领域:
- 泌尿器科 泌尿器科 泌尿器科 泌尿器科
- 手术技术 手术技术
- 医疗成像医学成像
背景情况:
- 评估外科专业能力对于培训和患者安全至关重要.
- 缺乏客观的实时工具来评估内镜石材操作能力.
- 计算机视觉模型为客观绩效评估提供了一个潜在的解决方案.
研究的目的:
- 应用内镜计算机视觉模型用于自动化性能指标 (APM).
- 从结石治疗的柔性尿路透镜手术视频中定义APM.
- 为了比较外科专家和实习生之间的APM.
主要方法:
- 评估了三个APM:没有石头的框架%,石头屏幕占用率和石头占用率的框架对框架的变化.
- 分析了石头定位和激光切除的手术视频.
- 用一个经过验证的计算机视觉模型来进行内镜石块细分.
主要成果:
- 实习生石头定位视频显示了比专家更多的没有可见石头的和更低的石头屏幕占用率.
- 与专家相比,实习者激光切除视频显示石头占用率的对变化更高.
- 在专家和实习生绩效指标之间观察到显著差异 (p < 0.01).
结论:
- 从计算机视觉获得的自动化性能指标在专家外科医生和实习外科医生之间有所不同.
- 这些APM可以客观地评估内镜结石治疗中的技能获取.
- 这项技术有望提高外科培训和患者安全.
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