Problem
Research questions and friction points this paper is trying to address.
surgical performance assessment
tissue handling
minimally invasive surgery
Beyond Instrument Motion: Recognizing Tissue Tension Toward Surgical Skill Assessment
🤖 AI Summary
为解决微创手术技能评估中组织张力识别问题，构建了SurgTension数据集，并提出基于轨迹的TensionTRAC框架以自动识别组织张力。
📝 Abstract
Surgical performance assessment in minimally invasive surgery largely relies on manual expert review, making it time-consuming, subjective, and difficult to scale. While existing surgical video understanding methods address tasks such as instrument segmentation, surgical phase recognition, and action recognition, they do not explicitly capture fine-grained tissue handling, a key indicator of surgical quality. To address this gap, we introduce tissue tension recognition, a new clinically motivated video understanding task for laparoscopic and robot-assisted rectal cancer surgery. To support this task, we construct SurgTension, the first expert-annotated tissue tension dataset, providing a benchmark for objective tissue tension recognition. We further propose TensionTRAC, a lightweight trajectory-based framework that models tissue tension from sparse point trajectories. Using a compact trajectory encoder, TensionTRAC achieves competitive performance against strong pretrained video backbones.
Innovation
Methods, ideas, or system contributions that make the work stand out.
tissue tension recognition
SurgTension dataset
TensionTRAC framework
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