English(EN) TEDi: Temporal Memory-Enhanced and Denoising Transformer for Surgical Instrument Segmentation

新型Transformer模型增强手术器械分割

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-16 04:00

研究人员开发了TEDi，一种新颖的基于Transformer的手术器械分割模型。TEDi通过结合时间记忆增强和去噪技术，解决了现有基于查询方法的局限性。该模型利用查询级记忆库检索历史帧表示，并使用时间一致性参考来改善跨帧的语义连贯性，从而获得更稳定的预测。在EndoVis 2017和EndoVis 2018数据集上的实验表明，TEDi的表现优于当前最先进的方法，显示了其在推进计算机辅助手术方面的潜力。 AI

影响这项研究可能带来更准确、更稳定的手术器械识别，从而改进计算机辅助手术系统。

排序理由该集群描述了一篇关于为特定计算机视觉任务设计新颖模型的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.CV TIER_1 English(EN) · Jiahong Yuan, Weiming Mi, Tao Zhang, Haoyin Zhou · 2026-09-16 04:00

TEDi：用于手术器械分割的时间记忆增强和去噪Transformer

arXiv:2609.16797v1 Announce Type: new Abstract: Query-based segmentation methods have shown promising potential for surgical instrument segmentation and recognition, which is essential for scene understanding and downstream tasks in computer assisted surgery. However, most existi…

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TEDi：用于手术器械分割的时间记忆增强和去噪Transformer

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