客观评估的眼神位置模式使用眼睛跟踪在囊镜和人工智能辅助的损伤检测检测过程中
Atsushi Ikeda1, Kazuya Izumi2, Kensuke Katori2
1Department of Urology, Institute of Medicine, University of Tsukuba, Tsukuba, Ibaraki, Japan.
Journal of endourology
|March 25, 2024
概括
泌尿科医生在囊泡镜检查期间展示了高效的凝视模式,覆盖了比医学学生更多的膀表面. 人工智能 (AI) 通过在囊镜图像分析期间将他们的注意力转向病变来帮助医学学生.
科学领域:
- 泌尿器科 泌尿器科 泌尿器科 泌尿器科
- 医疗成像医学成像
- 人工智能在医学中的应用
背景情况:
- 囊镜的诊断准确性取决于医生.
- 专家和新手之间凝视模式的变化并未得到充分理解.
- 人工智能 (AI) 对囊镜视觉搜索策略的影响需要研究.
研究的目的:
- 为了比较泌尿科医生和医学学生之间的囊镜凝视位置模式.
- 在查看常规与人工智能辅助囊镜图像时,评估眼动的差异.
- 评估AI在导向视觉注意力时的实用性. 在囊镜.
主要方法:
- 用眼睛追踪测量分析了24名医学学生和10名泌尿科医生的观察模式.
- 参与者观看了膀癌的囊镜视频,包括常规和人工智能辅助的病变检测图像.
- 使用基于屏幕的凝视追踪系统记录了凝视视角坐标和停止时间.
主要成果:
- 泌尿科医生比医学学生表现出明显更高的静止凝视,这表明膀粘膜的视觉扫描范围更广.
- 医学专业的学生,与泌尿科医生不同,在将图像并排查看时,将更多的注意力集中在AI检测到的病变上.
- 人工智能辅助的病变检测影响了不那么有经验的观察者的凝视模式.
结论:
- 经验丰富的泌尿科医生在囊镜检查期间有效地扫描视频屏幕的更大区域.
- 人工智能引导的病变检测可以将医学学生的注意力转向相关领域.
- 眼睛追踪分析为视觉专业知识提供了洞察力,并有可能在囊镜培训中进行教育应用.
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