In vivo fluorescence spectra unmixing and autofluorescence removal by sparse Non-negative Matrix Factorization
Résumé
Fluorescence imaging locates fluorescent markers that specifically bind to targets, as tumors: markers are injected to a patient, optimally excited with near infrared light, and located thanks to emitted back fluorescence analysis. To investigate thick and diffusive media, as the fluorescence signal decreases with the light travel distance, the autofluorescence of biological tissues comes to be a limiting factor. To remove autofluorescence and isolate specific fluorescence, a spectroscopic approach, based on Non-negative Matrix Factorization (NMF), is explored. To improve results on spatially sparse markers detection, we suggest a new constrained NMF algorithm which takes sparsity constraints into account. A comparative study between both algorithms is proposed on simulated and in vivo data.
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