Hartenberger, Martin;
Ayaz, Huzeyfe;
Ozlugedik, Fatih;
Caredda, Charly;
Giannoni, Luca;
Lange, Frédéric;
Lux, Laurin;
... Ezhov, Ivan; + view all
(2026)
Redefining Spectral Unmixing for In-Vivo Brain Tissue Analysis from Hyperspectral Imaging.
In: Li, Chao and Qin, Wenjian and Wu, Jia and Zaki, Nazar, (eds.)
Computational Mathematics Modeling in Cancer Analysis, Proceedings.
(pp. pp. 40-49).
Springer, Cham: Cham, Switzerland.
(In press).
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2503.00198v3.pdf - Accepted Version Access restricted to UCL open access staff until 26 September 2026. Download (12MB) |
Abstract
In this paper, we propose a methodology for extracting molecular tumor biomarkers from hyperspectral imaging (HSI), an emerging technology for intraoperative tissue assessment. To achieve this, we employ spectral unmixing, allowing to decompose the spectral signals recorded by the HSI camera into their constituent molecular components. Traditional unmixing approaches are based on physical models that establish a relationship between tissue molecules and the recorded spectra. However, these methods commonly assume a linear relationship between the spectra and molecular content, which does not capture the whole complexity of light-matter interaction. To address this limitation, we introduce a novel unmixing procedure that allows to take into account non-linear optical effects while preserving the computational benefits of linear spectral unmixing. We validate our methodology on an in-vivo brain tissue HSI dataset and demonstrate that the extracted molecular information leads to superior classification performance
| Type: | Proceedings paper |
|---|---|
| Title: | Redefining Spectral Unmixing for In-Vivo Brain Tissue Analysis from Hyperspectral Imaging |
| Event: | 4th International Workshop, CMMCA 2025 |
| ISBN-13: | 978-3-032-06623-7 |
| DOI: | 10.1007/978-3-032-06624-4 |
| Publisher version: | https://doi.org/10.1007/978-3-032-06624-4_5 |
| Language: | English |
| Additional information: | This version is the author-accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Hyperspectral imaging, Brain surgery, Spectral Unmixing. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Med Phys and Biomedical Eng |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10216074 |
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