most citedHandling Geometric Domain Shifts in Semantic Segmentation of Surgical RGB and Hyperspectral Images

1 citations · 1 across the 1 of their papers we have counts for

collaborators

5 papers

cs.CV2025

CARL: Camera-Agnostic Representation Learning for Spectral Image Analysis

Alexander Baumann, Leonardo Ayala, Silvia Seidlitz +5

Spectral imaging offers promising applications across diverse domains, including medicine and urban scene understanding, and is already established as a critical modality in remote…

cs.CV2024

Beyond Knowledge Silos: Task Fingerprinting for Democratization of Medical Imaging AI

Patrick Godau, Akriti Srivastava, Constantin Ulrich +3

The field of medical imaging AI is currently undergoing rapid transformations, with methodical research increasingly translated into clinical practice. Despite these successes, res…

cs.CV2024

Xeno-learning: knowledge transfer across species in deep learning-based spectral image analysis

Jan Sellner, Alexander Studier-Fischer, Ahmad Bin Qasim +16

Novel optical imaging techniques, such as hyperspectral imaging (HSI) combined with machine learning-based (ML) analysis, have the potential to revolutionize clinical surgical imag…

eess.IV2024

Deep intra-operative illumination calibration of hyperspectral cameras

Alexander Baumann, Leonardo Ayala, Alexander Studier-Fischer +6

Hyperspectral imaging (HSI) is emerging as a promising novel imaging modality with various potential surgical applications. Currently available cameras, however, suffer from poor i…

cs.CV20241 cited

Handling Geometric Domain Shifts in Semantic Segmentation of Surgical RGB and Hyperspectral Images

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

Robust semantic segmentation of intraoperative image data holds promise for enabling automatic surgical scene understanding and autonomous robotic surgery. While model development…