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.

翻译：套管端口是相机固定的伪静态结构，其镜面纹理表面会持续遮挡腹腔镜视野并吸引过多特征点。这使得端口对基于几何的下游流程（如图像拼接、三维重建和视觉SLAM）尤为不利，其中动态或非解剖结构的异常值会降低配准和跟踪稳定性。尽管具有实际重要性，公开手术数据集中鲜有显式端口标注，且现有标注常因遮蔽中央管腔（开口）而违反几何一致性，即使解剖区域可通过该开口可见。本文提出Cholec80-port——一个源自Cholec80的高保真套管端口分割数据集，同时制定了排除中央开口的端口套管掩膜标准操作程序。我们基于同一SOP对现有公开数据集进行了清洗与统一。实验表明，几何一致性标注能显著提升跨数据集鲁棒性，其效果超越单纯扩大数据集规模所能达到的增益。