构建首个几何一致的手术孔口分割数据集，提升腹腔镜视觉理解稳定性。
Cholec80-port: A Geometrically Consistent Trocar Port Segmentation Dataset for Robust Surgical Scene Understanding
- 定义统一标注标准，排除孔口中心开口，确保几何一致性。
- 在跨数据集测试中，一致标注使模型鲁棒性显著优于单纯增加数据量。
- 适用于需要精准3D重建与图像拼接的智能手术系统开发。
Trocar ports 是固定于摄像头的伪静态结构，其反光且纹理丰富的表面易吸引大量特征点，长期遮挡视野，严重影响基于几何的下游任务（如图像拼接、3D重建和视觉SLAM）的对齐与跟踪稳定性。尽管其重要性突出，公开手术数据集中显式标注的孔口极少，且现有标注常因遮盖中心开口而破坏几何一致性，即使解剖区域可见。本文提出 Cholec80-port，基于 Cholec80 构建的高保真孔口分割数据集，并制定严格的标准操作流程（SOP），定义孔口袖套掩码时排除中央开口。同时，依据该 SOP 清洗并统一现有公开数据集。实验表明，几何一致的标注可显著提升跨数据集鲁棒性，效果超越仅依赖数据规模扩大。
原文摘要 · Abstract (English)
Trocar ports are camera-fixed, pseudo-static structures that can persistently occlude laparoscopic views and attract disproportionate feature points due to specular, textured surfaces. This makes ports particularly detrimental to geometry-based downstream pipelines such as image stitching, 3D reconstruction, and visual SLAM, where dynamic or non-anatomical outliers degrade alignment and tracking stability. Despite this practical importance, explicit port labels are rare in public surgical datasets, and existing annotations often violate geometric consistency by masking the central lumen (opening), even when anatomical regions are visible through it. We present Cholec80-port, a high-fidelity trocar port segmentation dataset derived from Cholec80, together with a rigorous standard operating procedure (SOP) that defines a port-sleeve mask excluding the central opening. We additionally cleanse and unify existing public datasets under the same SOP. Experiments demonstrate that geometrically consistent annotations substantially improve cross-dataset robustness beyond what dataset size alone provides.
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