196 citations · 264 across the 11 of their papers we have counts for
11 papers
OSS: Open Suturing Skills Vision-Based Assessment Challenge 2024-2025
Hanna Hoffmann, Setareh Bady, Claas de Boer +54
Achieving high levels of surgical skill through effective training is essential for optimal patient outcomes. Automated, data-driven skill assessment holds significant potential to…
A benchmark for video-based laparoscopic skill analysis and assessment
Isabel Funke, Sebastian Bodenstedt, Felix von Bechtolsheim +7
Laparoscopic surgery is a complex surgical technique that requires extensive training. Recent advances in deep learning have shown promise in supporting this training by enabling a…
Mission Balance: Generating Under-represented Class Samples using Video Diffusion Models
Danush Kumar Venkatesh, Isabel Funke, Micha Pfeiffer +5
Computer-assisted interventions can improve intra-operative guidance, particularly through deep learning methods that harness the spatiotemporal information in surgical videos. How…
TUNeS: A Temporal U-Net with Self-Attention for Video-based Surgical Phase Recognition
Isabel Funke, Dominik Rivoir, Stefanie Krell +1
Objective: To enable context-aware computer assistance in the operating room of the future, cognitive systems need to understand automatically which surgical phase is being perform…
Metrics Matter in Surgical Phase Recognition
Isabel Funke, Dominik Rivoir, Stefanie Speidel
Surgical phase recognition is a basic component for different context-aware applications in computer- and robot-assisted surgery. In recent years, several methods for automatic sur…
On the Pitfalls of Batch Normalization for End-to-End Video Learning: A Study on Surgical Workflow Analysis
Dominik Rivoir, Isabel Funke, Stefanie Speidel
Batch Normalization's (BN) unique property of depending on other samples in a batch is known to cause problems in several tasks, including sequence modeling. Yet, BN-related issues…