Simultaneous decomposition of multiple hyperspectral data sets: signal recovery of unknown fluorophores in the retinal pigment epithelium.

Upon excitation with different wavelengths of light, biological tissues emit distinct but related autofluorescence signals. We used non-negative matrix factorization (NMF) to simultaneously decompose co-registered hyperspectral emission data from human retinal pigment epithelium/Bruch's membrane specimens illuminated with 436 and 480 nm light. NMF analysis was initialized with Gaussian mixture model fits and constrained to provide identical abundance images for the two excitation wavelengths. Spectra recovered this way were smoother than those obtained separately; fluorophore abundances more clearly localized within tissue compartments. These studies provide evidence that leveraging multiple co-registered hyperspectral emission data sets is preferential for identifying biologically relevant fluorophore information.