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20212025
most citedRobust deep learning-based semantic organ segmentation in hyperspectral images

92 citations · 96 across the 5 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★ 1 cited

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★ 3 cited

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…

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…

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…