Lars Wagner
5 Papers
1 Citations
Lars Wagner is an academic researcher. The author has contributed to research in topics: Medicine & Geology. The author has an hindex of 1, co-authored 3 publications.
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Papers
Deep learning assisted intraoperative instrument cleaning station for robotic scrub nurse systems
Lars Wagner,Lukas Bernhard,Alissa Jell,D. Wilhelm +3 more
- 01 Jul 2023
TL;DR: In this article , the authors presented a cleaning station for robotic scrub nurse systems which provides intraoperative cleaning of laparoscopic instruments during minimally invasive procedures, using deep learning to decide autonomously on the need of intra-operative cleaning to preserve instrument functions.
3
Integrating 3D cameras into sterile surgical environments: A comparison of different protective materials regarding scan accuracy
Lars Wagner,Lukas Bernhard,Jonas Fuchtmann,Mert Asim Karaoglu,Alexander Ladikos,Hubertus Feussner,D. Wilhelm +6 more
TL;DR: This work presents a sterile concept for 3D cameras within sterile surgical environments, whereby hygienic requirements need to be met, and compares the effect of using different pane types and thicknesses for the sterile camera enclosure and compared the performance with and without protective pane.
1
Correction to: Versatile end effector for laparoscopic robotic scrub nurse.
Lars Wagner,Christian Looschen,Lukas Bernhard,Jonas Fuchtmann,Maximilian Berlet,Johannes Fottner,Alois Christian Knoll,D. Wilhelm +7 more
TL;DR: The original version of this article unfortunately contained a mistake and the correct given name and family name should be Lars.
On the notion of missingness for path attribution explainability methods in medical settings: Guiding the selection of medically meaningful baselines
Alexander Geiger,Lars Wagner,Daniel Rueckert,Dirk Wilhelm,Alissa Jell +4 more
TL;DR: This study addresses the challenge of selecting meaningful baselines for path attribution methods in medical settings, introducing a counterfactual-guided approach using Variational Autoencoders to generate clinically relevant baselines for improved explainability and transparency.
Video-based multi-target multi-camera tracking for postoperative phase recognition.
Franziska Jurosch,Janik Zeller,Lars Wagner,Ege Özsoy,Alissa Jell,Sven Kolb,D. Wilhelm +6 more
TL;DR: This study proposes a novel multi-target multi-camera tracking architecture for postoperative phase recognition, location tracking, and timestamp generation, achieving 84.9% traversal accuracy, 91.4% correct timestamp generation, and 92.0% patient tracking IDF1 in a simulated postoperative setting.