activity
20242026
collaborators

10 papers

cs.CV2026

Surgical Anatomy Recognition with Context Learning using Foundation Representations

Ronald L. P. D. de Jong, Tim J. M. Jaspers, Raf A. H. Vervoort +9

Accurate recognition of anatomical structures is essential for safe and effective minimally invasive surgery (MIS), yet it remains underexplored in surgical computer vision due to…

cs.CV2026

Object Tokens as a Bridge Between Segmentation and Visual Question Answering in Robotic Surgery

Yiping Li, Ronald de Jong, Romy van Jaarsveld +5

Visual Question Answering (VQA) in robotic surgery, referred to as surgical VQA, requires high-level understanding of complex surgical scenes and the integration of visual percepti…

cs.CV2026

Comparative validation of surgical phase recognition, instrument keypoint estimation, and instrument instance segmentation in endoscopy: Results of the PhaKIR 2024 challenge

Tobias Rueckert, David Rauber, Raphaela Maerkl +58

Reliable recognition and localization of surgical instruments in endoscopic video recordings are foundational for a wide range of applications in computer- and robot-assisted minim…

cs.CV2025

SAM-Fed: SAM-Guided Federated Semi-Supervised Learning for Medical Image Segmentation

Sahar Nasirihaghighi, Negin Ghamsarian, Yiping Li +3

Medical image segmentation is clinically important, yet data privacy and the cost of expert annotation limit the availability of labeled data. Federated semi-supervised learning (F…

eess.IV2025

Analysis of Transferability Estimation Metrics for Surgical Phase Recognition

Prabhant Singh, Yiping Li, Yasmina Al Khalil

Fine-tuning pre-trained models has become a cornerstone of modern machine learning, allowing practitioners to achieve high performance with limited labeled data. In surgical video…

cs.CV2025

SemiVT-Surge: Semi-Supervised Video Transformer for Surgical Phase Recognition

Yiping Li, Ronald de Jong, Sahar Nasirihaghighi +8

Accurate surgical phase recognition is crucial for computer-assisted interventions and surgical video analysis. Annotating long surgical videos is labor-intensive, driving research…