Xeno-learning: knowledge transfer across species in deep learning-based spectral image analysis
Optical imaging techniques, such as hyperspectral imaging combined with machine learning-based analysis, have the potential to revolutionize clinical surgical imaging. However, these modalities face a shortage of large-scale, representative clinical data for training machine learning-based algorithm...
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| Main Authors: | , , , , , , , , , , , , , , , , , , |
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| Format: | Article (Journal) |
| Language: | English |
| Published: |
26 January 2026
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| In: |
Nature biomedical engineering
Year: 2026, Pages: 1-15 |
| ISSN: | 2157-846X |
| DOI: | 10.1038/s41551-025-01585-4 |
| Online Access: | Verlag, kostenfrei, Volltext: https://doi.org/10.1038/s41551-025-01585-4 Verlag, kostenfrei, Volltext: https://www.nature.com/articles/s41551-025-01585-4 
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| Author Notes: | Jan Sellner, Alexander Studier-Fischer, Ahmad Bin Qasim, Silvia Seidlitz, Nicholas Schreck, Minu Tizabi, Manuel Wiesenfarth, Annette Kopp-Schneider, Janne Heinecke, Jule Brandt, Samuel Knoedler, Caelan Max Haney, Gabriel Salg, Berkin Özdemir, Maximilian Dietrich, Maurice Stephan Michel, Felix Nickel, Karl-Friedrich Kowalewski & Lena Maier-Hein |
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Xeno-learning: knowledge transfer across species in deep learning-based spectral image analysis
[2026?]
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Xeno-learning: knowledge transfer across species in deep learning-based spectral image analysis
Universitätsbibliothek Heidelberg 17 Feb. 2026
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