activity
20202025
most citedXCAT-GAN for Synthesizing 3D Consistent Labeled Cardiac MR Images on Anatomically Variable XCAT Phantoms

22 citations · 22 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CV2025

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 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…

eess.IV202022 cited

XCAT-GAN for Synthesizing 3D Consistent Labeled Cardiac MR Images on Anatomically Variable XCAT Phantoms

Sina Amirrajab, Samaneh Abbasi-Sureshjani, Yasmina Al Khalil +4

Generative adversarial networks (GANs) have provided promising data enrichment solutions by synthesizing high-fidelity images. However, generating large sets of labeled images with…