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20212025
most citedExploring Semantic Consistency in Unpaired Image Translation to Generate Data for Surgical Applications

2 citations · 2 across the 6 of their papers we have counts for

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cs.CV2025

PIVOTS: Aligning unseen Structures using Preoperative to Intraoperative Volume-To-Surface Registration for Liver Navigation

Peng Liu, Bianca Güttner, Yutong Su +16

Non-rigid registration is essential for Augmented Reality guided laparoscopic liver surgery by fusing preoperative information, such as tumor location and vascular structures, into…

cs.CV2025

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…

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

Data Augmentation for Surgical Scene Segmentation with Anatomy-Aware Diffusion Models

Danush Kumar Venkatesh, Dominik Rivoir, Micha Pfeiffer +2

In computer-assisted surgery, automatically recognizing anatomical organs is crucial for understanding the surgical scene and providing intraoperative assistance. While machine lea…

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…

cs.CV2023★ 2 cited

Exploring Semantic Consistency in Unpaired Image Translation to Generate Data for Surgical Applications

Danush Kumar Venkatesh, Dominik Rivoir, Micha Pfeiffer +4

In surgical computer vision applications, obtaining labeled training data is challenging due to data-privacy concerns and the need for expert annotation. Unpaired image-to-image tr…