title: In vivo fluorescence spectra unmixing and autofluorescence removal by sparse nonnegative matrix factorization.
abstract: Fluorescence imaging locates fluorescent markers that specifically bind to targets; like tumors, markers are injected to a patient, optimally excited with near-infrared light, and located thanks to backward-emitted fluorescence analysis. To investigate thick and diffusive media, as the fluorescence signal decreases exponentially 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 nonnegative matrix factorization (NMF), is explored. To improve results on spatially sparse markers detection, we suggest a new constrained NMF algorithm that takes sparsity constraints into account. A comparative study between both algorithms is proposed on simulated and in vivo data.
authors.affiliation: CEA, LETI, MINATEC, 38054 Grenoble cedex 9, France. as.montcuquet@gmail.com
authors.forename: Anne-Sophie
authors.initials: AS
authors.lastname: Montcuquet
authors.forename: Lionel
authors.initials: L
authors.lastname: Hervé
authors.forename: Fabrice
authors.initials: F
authors.lastname: Navarro
authors.forename: Jean-Marc
authors.initials: JM
authors.lastname: Dinten
authors.forename: Jérôme I
authors.initials: JI
authors.lastname: Mars
mesh_terms: D000465:Algorithms; D000818:Animals; D001943:Breast Neoplasms / Q000175:diagnosis; D003198:Computer Simulation; D003952:Diagnostic Imaging / Q000379:methods*; D005240:Feasibility Studies; D005260:Female; D005453:Fluorescence; D006801:Humans; D007208:Indocyanine Green / Q000737:chemistry; D051379:Mice; D008819:Mice, Nude; D008954:Models, Biological; D012815:Signal Processing, Computer-Assisted; D013050:Spectrometry, Fluorescence / Q000379:methods*; D013388:Succinimides / Q000737:chemistry
chemical_list: C502599:Alexa Fluor 750; D013388:Succinimides; D007208:Indocyanine Green