为巴雷特食道内镜进行计算机辅助质量控制系统的开发和实体评估
Martijn R Jong1, Tim J M Jaspers2, Rixta A H van Eijck van Heslinga1
1Department of Gastroenterology and Hepatology, Amsterdam Gastroenterology, Endocrinology and Metabolism, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands.
Endoscopy
|February 11, 2025
概括
针对巴雷特食道 (BE) 的新计算机辅助质量 (CAQ) 系统改善了内镜图像评估. 将CAQ与计算机辅助检测 (CADe) 整合起来,可以提高BE患者的瘤检测.
科学领域:
- 胃肠病学 胃肠病学
- 医疗成像医学成像
- 人工智能的人工智能
背景情况:
- 在巴雷特食道 (BE) 中及时检测瘤是具有挑战性的.
- 计算机辅助检测 (CADe) 系统提高了检测,但依赖于高质量的内镜图像.
- 内镜手术的质量显著影响了CADe系统的有效性.
研究的目的:
- 开发和评估一个新的计算机辅助质量 (CAQ) 系统,用于BE.
- 评估CAQ系统的独立性能.
- 评估CAQ系统与CADe系统的集成,以改善瘤检测.
主要方法:
- 开发了一个CAQ系统,使用359名BE患者的7,463张图像.
- 评估客观 (模糊,照明) 和主观 (粘膜清洁,膨胀) 质量参数.
- 评估CAQ作为独立工具和作为CADe系统的预处理过器,使用专用测试集.
主要成果:
- 在图像质量评估方面,CAQ系统与人类注释者达成了很高的一致性 (Cohen's Kappa: 0.73-0.91).
- 作为预处理过器,CAQ集成将CADe灵敏度从82%提高到90%,AUC从87%提高到91%.
- 当与CAQ系统集成时,CADe的特异性保持在75%的稳定水平.
结论:
- 本研究介绍了首个用于自动化质量控制的CAQ系统.
- 该CAQ系统有效地区分了可视化良好和可视化不良的粘膜.
- 将CAQ与CADe集成,可以提高BE中瘤的检测,提高诊断准确度.
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