collaborators

5 papers

cs.CV2025

XiCAD: Camera Activation Detection in the Da Vinci Xi User Interface

Alexander C. Jenke, Gregor Just, Claas de Boer +3

Purpose: Robot-assisted minimally invasive surgery relies on endoscopic video as the sole intraoperative visual feedback. The DaVinci Xi system overlays a graphical user interface…

cs.CV2025

Federated Learning for Surgical Vision in Appendicitis Classification: Results of the FedSurg EndoVis 2024 Challenge

Max Kirchner, Hanna Hoffmann, Alexander C. Jenke +16

Developing generalizable surgical AI requires multi-institutional data, yet privacy constraints preclude direct data sharing, making Federated Learning (FL) a natural candidate. It…

cs.LG2025

Adversarial Subspace Generation for Outlier Detection in High-Dimensional Data

Jose Cribeiro-Ramallo, Federico Matteucci, Paul Enciu +4

Outlier detection in high-dimensional tabular data is challenging since data is often distributed across multiple lower-dimensional subspaces -- a phenomenon known as the Multiple…

cs.CV2025

Federated EndoViT: Pretraining Vision Transformers via Federated Learning on Endoscopic Image Collections

Max Kirchner, Alexander C. Jenke, Sebastian Bodenstedt +5

Purpose: Data privacy regulations hinder the creation of generalizable foundation models (FMs) for surgery by preventing multi-institutional data aggregation. This study investigat…

cs.CV2024

One model to use them all: Training a segmentation model with complementary datasets

Alexander C. Jenke, Sebastian Bodenstedt, Fiona R. Kolbinger +3

Understanding a surgical scene is crucial for computer-assisted surgery systems to provide any intelligent assistance functionality. One way of achieving this scene understanding i…