activity
20242026
collaborators

5 papers

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

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…

cs.CV2025

Scaling up self-supervised learning for improved surgical foundation models

Tim J. M. Jaspers, Ronald L. P. D. de Jong, Yiping Li +12

Foundation models have revolutionized computer vision by achieving vastly superior performance across diverse tasks through large-scale pretraining on extensive datasets. However,…

cs.CV2024

Benchmarking Pretrained Attention-based Models for Real-Time Recognition in Robot-Assisted Esophagectomy

Ronald L. P. D. de Jong, Yasmina al Khalil, Tim J. M. Jaspers +7

Esophageal cancer is among the most common types of cancer worldwide. It is traditionally treated using open esophagectomy, but in recent years, robot-assisted minimally invasive e…

cs.CV2024

Benchmarking and Enhancing Surgical Phase Recognition Models for Robotic-Assisted Esophagectomy

Yiping Li, Romy van Jaarsveld, Ronald de Jong +6

Robotic-assisted minimally invasive esophagectomy (RAMIE) is a recognized treatment for esophageal cancer, offering better patient outcomes compared to open surgery and traditional…