arXiv Computer Vision
Aug 25

Dense Structural Priors for Sparse Functional Landmark Localization in Surgical Videos

The paper presents a method for localizing functional surgical landmarks—specifically instrument tips and anchors—in surgical videos without requiring manual pixel-level mask annotations. It leverages vision foundation models, such as SAM 3, to generate dense structural priors through zero‑shot, point‑prompted masks, and refines landmark predictions with a lightweight, coarse‑to‑fine multi‑frame network. Experiments on 7,867 clips from 60 videos show that the approach achieves F1 scores of 72.4% for tip and 58.0% for anchor localization, with ablations confirming the benefits of structural priors and refinement stages.

By Chenyan Jing, Hao Ding, Lalithkumar Seenivasan, Jacob M. Delgado L\'opez, Mathias Unberath
arXiv Machine Learning
Aug 3

Leveraging Transfer Learning with Class-Specific Decoders for Laparoscopic Segmentation

arXiv:2607. 29509v1 Announce Type: cross Abstract: Effective multi-organ segmentation in surgical data requires learning the intricate anatomical features and alleviating the challenge of class imbalance, which results from relatively lower proportions of small and limitedly exposed structures.

By Priya Tomar, Aditya Parikh, Christian Bauckhage, Rafet Sifa
arXiv Computer Vision
3d ago

Rethinking Data Imbalance in Class Incremental Surgical Instrument Segmentation

arXiv:2610.34925v1 Announce Type: new Abstract: In surgical instrument segmentation, the increasing variety of instruments over time poses a significant challenge for existing neural networks, as the...

By Shifang Zhao, Long Bai, Kun Yuan, Feng Li, Jieming Yu, Wenzhen Dong, Guankun Wang, Mobarakol Islam, Nicolas Padoy, Nassir Navab, Hongliang Ren
arXiv Computer Vision
Sep 10

Synergistic Vision-Language Reinforcement Enables Scalable On-Demand Analysis across Diverse Clinical Tasks

arXiv:2505.03380v2 Announce Type: replace Abstract: Accurate delineation of tumors and surrounding organs-at-risk is essential for radiotherapy, surgery and treatment response assessment, yet remains...

By Haonan Wang, Jiaji Mao, Lehan Wang, Qixiang Zhang, Marawan Elbatel, Yi Qin, Huijun Hu, Baoxun Li, Wenhui Deng, Weifeng Qin, Hongrui Li, Jialin Liang, Jun Shen, Xiaomeng Li