Non-negative Matrix Factorization under sparsity constraints to unmix in vivo spectrally resolved acquisitions

Anne-Sophie Montcuquet (1, 2) , Lionel Herve (2) , Fabrice Navarro (2) , Jean-Marc Dinten (2) , Jerome I. Mars (1)

1 GIPSA-SIGMAPHY - GIPSA - Signal Images Physique
2 CEA-LETI - Commissariat à l'énergie atomique et aux énergies alternatives - Laboratoire d'Electronique et de Technologie de l'Information

Fluorescence imaging in diffusive media is an emerging imaging modality for medical applications which uses injected fluorescent markers (several ones may be simultaneously injected) that bind to specific targets, as tumors. The region of interest is illuminated with near infrared light and the emitted back fluorescence is analyzed to localize the fluorescence sources. To investigate thick medium, as the fluorescence signal decreases with the light travel distance, any disturbing signal, such as biological tissues intrinsic fluorescence - called autofluorescence -, is a limiting factor. To remove autofluorescence and isolate each specific fluorescent signal from the others, a spectroscopic approach, based on Non-negative Matrix Factorization, is explored. We ran an NMF algorithm with sparsity constraints on experimental data, and successfully obtained separated in vivo fluorescence spectra.

Domaines: Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]

Anne-Sophie Montcuquet, Lionel Herve, Fabrice Navarro, Jean-Marc Dinten, Jerome I. Mars. Non-negative Matrix Factorization under sparsity constraints to unmix in vivo spectrally resolved acquisitions. WHISPERS 2010 - 2nd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, Jun 2010, Reykjavik, Iceland. pp.30. ⟨hal-00625417⟩