论文标题
使用计算机视觉自动化手术视频中的手部检测和跟踪外科医生的运动
Using Computer Vision to Automate Hand Detection and Tracking of Surgeon Movements in Videos of Open Surgery
论文作者
论文摘要
开放或非肾上腺镜手术代表了所有手术室程序中的绝大多数，但是几乎没有工具可以客观地评估这些技术。当前的努力涉及基于人类专家的视觉评估。我们利用计算机视觉的进步来引入一种自动化方法，以进行手术执行的视频分析。用于对象检测的最先进的卷积神经网络体系结构用于检测开放手术视频中的手术手。通过将模型预测与快速对象跟踪器相结合以实现外科医生特定的手部跟踪来扩展自动化评估。为了培训我们的模型，我们使用了YouTube的公开开放手术视频，并用空间边界的操作盒对这些视频进行了注释。我们的模型对手术手的空间检测极大地超过了使用先前存在的手提检测数据集实现的检测，并可以深入了解术中运动模式和运动经济。
Open, or non-laparoscopic surgery, represents the vast majority of all operating room procedures, but few tools exist to objectively evaluate these techniques at scale. Current efforts involve human expert-based visual assessment. We leverage advances in computer vision to introduce an automated approach to video analysis of surgical execution. A state-of-the-art convolutional neural network architecture for object detection was used to detect operating hands in open surgery videos. Automated assessment was expanded by combining model predictions with a fast object tracker to enable surgeon-specific hand tracking. To train our model, we used publicly available videos of open surgery from YouTube and annotated these with spatial bounding boxes of operating hands. Our model's spatial detections of operating hands significantly outperforms the detections achieved using pre-existing hand-detection datasets, and allow for insights into intra-operative movement patterns and economy of motion.
