标题： 面向整体的外科场景图 显示英文标题

标题： Towards Holistic Surgical Scene Graph

摘要： 外科场景理解对于计算机辅助干预系统至关重要，需要对包含手术工具、解剖结构及其相互作用等多样化元素的外科场景进行视觉理解。 为了有效表示外科场景中的复杂信息，基于图的方法已被探索用于结构化建模外科实体及其关系。 先前的外科场景图研究已经证明了使用图来表示外科场景的可行性。 然而，尽管这些方面非常重要，外科场景中的一些方面，如工具-动作-目标的多样化组合以及操作工具的手的身份，在基于图的表示中仍缺乏深入研究。 为了将这些方面纳入图表示中，我们提出了 Endoscapes-SG201数据集，其中包含工具-动作-目标组合和手身份的注释。 我们还介绍了SSG-Com，这是一种基于图的方法，旨在学习和表示这些关键要素。 通过在下游任务（如安全评估的关键视图和动作三元组识别）上的实验，我们证明了整合这些重要场景图组件的重要性，突显了它们对外科场景理解的重要贡献。 代码和数据集可在 https://github.com/ailab-kyunghee/SSG-Com 获取。 显示英文摘要

摘要： Surgical scene understanding is crucial for computer-assisted intervention systems, requiring visual comprehension of surgical scenes that involves diverse elements such as surgical tools, anatomical structures, and their interactions. To effectively represent the complex information in surgical scenes, graph-based approaches have been explored to structurally model surgical entities and their relationships. Previous surgical scene graph studies have demonstrated the feasibility of representing surgical scenes using graphs. However, certain aspects of surgical scenes-such as diverse combinations of tool-action-target and the identity of the hand operating the tool-remain underexplored in graph-based representations, despite their importance. To incorporate these aspects into graph representations, we propose Endoscapes-SG201 dataset, which includes annotations for tool-action-target combinations and hand identity. We also introduce SSG-Com, a graph-based method designed to learn and represent these critical elements. Through experiments on downstream tasks such as critical view of safety assessment and action triplet recognition, we demonstrated the importance of integrating these essential scene graph components, highlighting their significant contribution to surgical scene understanding. The code and dataset are available at https://github.com/ailab-kyunghee/SSG-Com