眼睛追踪分析,以确定内镜师对人工智能检测到的结肠镜位点的识别率
Fumiaki Ishibashi1,2, Sho Suzuki3,4, Kentaro Mochida3,4
1Department of Gastroenterology, International University of Health and Welfare Ichikawa Hospital, 6-1-14 Konodai, Ichikawa-Shi, Chiba, 272-0827, Japan. ishibashi-gast@iuhw.ac.jp.
内镜师在结肠镜检查中识别了大多数计算机辅助检测 (CADe) 部位,但错过了一些文物. 状状病变 (SSLs) 需要谨慎注意,即使有CADe支持.
科学领域:
- 胃肠病学 胃肠病学
- 医疗成像医学成像
- 内镜检查是指内镜检查.
背景情况:
- 计算机辅助检测 (CADe) 系统有助于查结肠镜.
- 缺乏对CADe识别部位的内镜师识别的定量分析.
研究的目的:
- 量化评估内镜师在结肠镜检查期间通过CADe识别的部位的识别.
- 为了确定内镜师在多大程度上识别CADe检测到的候选部位.
主要方法:
- 使用眼睛追踪技术在结肠镜撤出的前性研究.
- 记录了内镜师的眼睛位置和CADe检测点.
- 计算识别速率 (注视>300毫秒) 并使用后勤回归来确定更快检测的预测因素.
主要成果:
- 在447个CADe检测到的部位中,内镜的整体识别率为82.1%.
- 腺瘤 (95.9%),高可塑性息肉 (92.8%),SSL (100%) 和粘膜内癌 (100%) 的识别率很高.
- 文物识别能力较低 (75.8%);只有33.3%的CADe检测到的SSL在300 ms内被跟踪.
结论:
- 内镜师有效地识别了大多数CADe识别的病变,但忽略了许多文物.
- 检测到状状病变 (SSL) 需要谨慎,即使使用CADe辅助.
- 结果提供了洞察力在结肠镜检查期间的CADe-endoscopist互动.
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