构建首个面向开放手术视频的精细手-工具分割数据集，助力手术行为理解。
EgoSurgery-HTS: A Dataset for Egocentric Hand-Tool Segmentation in Open Surgery Videos
- 采集并标注14类手术工具、双手及交互关系的像素级数据
- 在新数据集上手部与手-工具分割精度显著提升
- 适合研究手术视觉理解、机器人辅助手术的学者使用
眼动视角开放手术视频包含丰富细微信息，对精准建模手术流程和术者行为至关重要。本文提出EgoSurgery-HTS数据集，提供像素级标注与基准评测体系，支持（1）14类不同手术工具的实例分割，（2）双手实例分割，（3）手-工具交互分割。基于该数据集，我们对前沿分割方法进行了全面评估，结果显示在眼动视角开放手术视频中，手部及手-工具分割精度较现有数据集有显著提升。数据集将发布于https://github.com/Fujiry0/EgoSurgery。
原文摘要 · Abstract (English)
Egocentric open-surgery videos capture rich, fine-grained details essential for accurately modeling surgical procedures and human behavior in the operating room. A detailed, pixel-level understanding of hands and surgical tools is crucial for interpreting a surgeon's actions and intentions. We introduce EgoSurgery-HTS, a new dataset with pixel-wise annotations and a benchmark suite for segmenting surgical tools, hands, and interacting tools in egocentric open-surgery videos. Specifically, we provide a labeled dataset for (1) tool instance segmentation of 14 distinct surgical tools, (2) hand instance segmentation, and (3) hand-tool segmentation to label hands and the tools they manipulate. Using EgoSurgery-HTS, we conduct extensive evaluations of state-of-the-art segmentation methods and demonstrate significant improvements in the accuracy of hand and hand-tool segmentation in egocentric open-surgery videos compared to existing datasets. The dataset will be released at https://github.com/Fujiry0/EgoSurgery.
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