用视频自动检测肾镜训练中遗漏的肾盏，实现无需专家指导的训练反馈。
Automated Assessment of Kidney Ureteroscopy Exploration for Training
- 仅靠内窥镜视频构建参考模型，自动定位训练中镜头位置。
- 15次探索中识别出69/74个肾盏，定位误差小于4mm。
- 10分钟完成一次训练评估，适合无导师环境下的临床训练。
目的：肾输尿管镜导航难度大，学习曲线陡峭。但当前临床培训存在严重缺陷，需专家一对一反馈且局限于手术室（OR）。因此亟需一种具有自动反馈功能的模拟器以大幅扩展训练机会。方法：我们提出一种全新的、完全基于内窥镜视频的镜头定位框架，可自动识别训练者在模拟肾脏探索中遗漏的肾盏。利用对同一肾脏进行慢速、全面探索的先验视频生成参考重建模型，该模型可用于定位任意同源探索视频。结果：在15段探索视频中，共74个肾盏中有69个被正确分类，摄像头位姿定位误差低于4mm。在获得参考重建后，系统处理一段1-2分钟的典型探索视频耗时约10分钟。结论：我们展示了一种新型摄像机定位框架，能够为模拟肾镜探索提供准确、自动化的反馈。其有效性证明了该工具可作为无需专家监督的院外训练有效手段。
原文摘要 · Abstract (English)
Purpose: Kidney ureteroscopic navigation is challenging with a steep learning curve. However, current clinical training has major deficiencies, as it requires one-on-one feedback from experts and occurs in the operating room (OR). Therefore, there is a need for a phantom training system with automated feedback to greatly \revision{expand} training opportunities. Methods: We propose a novel, purely ureteroscope video-based scope localization framework that automatically identifies calyces missed by the trainee in a phantom kidney exploration. We use a slow, thorough, prior exploration video of the kidney to generate a reference reconstruction. Then, this reference reconstruction can be used to localize any exploration video of the same phantom. Results: In 15 exploration videos, a total of 69 out of 74 calyces were correctly classified. We achieve < 4mm camera pose localization error. Given the reference reconstruction, the system takes 10 minutes to generate the results for a typical exploration (1-2 minute long). Conclusion: We demonstrate a novel camera localization framework that can provide accurate and automatic feedback for kidney phantom explorations. We show its ability as a valid tool that enables out-of-OR training without requiring supervision from an expert.
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