activity
20182026
most citedRobust deep learning-based semantic organ segmentation in hyperspectral images

92 citations · 154 across the 9 of their papers we have counts for

collaborators

10 papers

cs.CV2026

Multimodal Assessment of Pancreatic Cancer Resectability Using Deep Learning

Vincent Ochs, Christoph Kuemmerli, Florentin Bieder +12

Accurate determination of pancreatic ductal adenocarcinoma (PDAC) resectability relies on evaluating how the tumor interacts with major peripancreatic vessels on CT imaging, yet ex…

cs.CV2023

Challenges in Multi-centric Generalization: Phase and Step Recognition in Roux-en-Y Gastric Bypass Surgery

Joel L. Lavanchy, Sanat Ramesh, Diego Dall'Alba +7

Most studies on surgical activity recognition utilizing Artificial intelligence (AI) have focused mainly on recognizing one type of activity from small and mono-centric surgical vi…

eess.IV2023

Semantic segmentation of surgical hyperspectral images under geometric domain shifts

Jan Sellner, Silvia Seidlitz, Alexander Studier-Fischer +5

Robust semantic segmentation of intraoperative image data could pave the way for automatic surgical scene understanding and autonomous robotic surgery. Geometric domain shifts, how…

cs.CV2022★ 3 cited

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…

eess.IV2021★ 92 cited

Robust deep learning-based semantic organ segmentation in hyperspectral images

Silvia Seidlitz, Jan Sellner, Jan Odenthal +11

Semantic image segmentation is an important prerequisite for context-awareness and autonomous robotics in surgery. The state of the art has focused on conventional RGB video data a…

cs.RO2021★ 23 cited

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…

cs.CV2021★ 3 cited

How can we learn (more) from challenges? A statistical approach to driving future algorithm development

Tobias Roß, Pierangela Bruno, Annika Reinke +12

Challenges have become the state-of-the-art approach to benchmark image analysis algorithms in a comparative manner. While the validation on identical data sets was a great step fo…

cs.CY2020

Surgical Data Science -- from Concepts toward Clinical Translation

Lena Maier-Hein, Matthias Eisenmann, Duygu Sarikaya +47

Recent developments in data science in general and machine learning in particular have transformed the way experts envision the future of surgery. Surgical Data Science (SDS) is a…

cs.CV2020★ 33 cited

Robust Medical Instrument Segmentation Challenge 2019

Tobias Ross, Annika Reinke, Peter M. Full +47

Intraoperative tracking of laparoscopic instruments is often a prerequisite for computer and robotic-assisted interventions. While numerous methods for detecting, segmenting and tr…

cs.CV2018

Prediction of laparoscopic procedure duration using unlabeled, multimodal sensor data

Sebastian Bodenstedt, Martin Wagner, Lars Mündermann +6

Purpose The course of surgical procedures is often unpredictable, making it difficult to estimate the duration of procedures beforehand. A context-aware method that analyses the wo…