Separable spectral unmixing based on the learning of periodic absorbance changes: application to functional brain mapping using RGB imaging

Charly Caredda; Jérémy E. Cohen; Laurent Mahieu-Williame; Raphaël Sablong; Michaël Sdika; Jacques Guyotat; Bruno Montcel

doi:10.1117/12.2670506

11 August 2023 Separable spectral unmixing based on the learning of periodic absorbance changes: application to functional brain mapping using RGB imaging

Charly Caredda, Jérémy E. Cohen, Laurent Mahieu-Williame, Raphaël Sablong, Michaël Sdika, Jacques Guyotat, Bruno Montcel

Author Affiliations +

Proceedings Volume 12627, Translational Biophotonics: Diagnostics and Therapeutics III; 126271D (2023) https://doi.org/10.1117/12.2670506
Event: European Conferences on Biomedical Optics, 2023, Munich, Germany

Abstract

Separable spectral unmixing designates techniques that allow to decompose spectra as a linear or non-linear combination of spectra of the targets (endmembers) collected. These techniques allow quantitative measurements but several drawbacks limit its use with standard optical devices like RGB cameras. We propose a new method for estimating endmembers and their proportion without calibration of the acquisition device with the analysis of periodic events in the signal. We evaluated the performances of the method for identifying functional brain areas during neurosurgery using RGB imaging. Results were consistent with clinical gold standards. This work can allow a widespread use of spectral imaging in the industrial or medical field.

Citation Download Citation

Charly Caredda, Jérémy E. Cohen, Laurent Mahieu-Williame, Raphaël Sablong, Michaël Sdika, Jacques Guyotat, and Bruno Montcel "Separable spectral unmixing based on the learning of periodic absorbance changes: application to functional brain mapping using RGB imaging", Proc. SPIE 12627, Translational Biophotonics: Diagnostics and Therapeutics III, 126271D (11 August 2023); https://doi.org/10.1117/12.2670506

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