578 citations · 851 across the 18 of their papers we have counts for
19 papers
Sim-To-Real Transfer for Visual Reinforcement Learning of Deformable Object Manipulation for Robot-Assisted Surgery
Paul Maria Scheikl, Eleonora Tagliabue, Balázs Gyenes +4
Automation holds the potential to assist surgeons in robotic interventions, shifting their mental work load from visuomotor control to high level decision making. Reinforcement lea…
Why is the winner the best?
Matthias Eisenmann, Annika Reinke, Vivienn Weru +122
International benchmarking competitions have become fundamental for the comparative performance assessment of image analysis methods. However, little attention has been given to in…
LapGym -- An Open Source Framework for Reinforcement Learning in Robot-Assisted Laparoscopic Surgery
Paul Maria Scheikl, Balázs Gyenes, Rayan Younis +4
Recent advances in reinforcement learning (RL) have increased the promise of introducing cognitive assistance and automation to robot-assisted laparoscopic surgery (RALS). However,…
Biomedical image analysis competitions: The state of current participation practice
Matthias Eisenmann, Annika Reinke, Vivienn Weru +352
The number of international benchmarking competitions is steadily increasing in various fields of machine learning (ML) research and practice. So far, however, little is known abou…
LapSeg3D: Weakly Supervised Semantic Segmentation of Point Clouds Representing Laparoscopic Scenes
Benjamin Alt, Christian Kunz, Darko Katic +5
The semantic segmentation of surgical scenes is a prerequisite for task automation in robot assisted interventions. We propose LapSeg3D, a novel DNN-based approach for the voxel-wi…
Cooperative Assistance in Robotic Surgery through Multi-Agent Reinforcement Learning
Paul Maria Scheikl, Balázs Gyenes, Tornike Davitashvili +6
Cognitive cooperative assistance in robot-assisted surgery holds the potential to increase quality of care in minimally invasive interventions. Automation of surgical tasks promise…