abstract

• The paper addresses the problem of identification of fluorescent molecules, or fluorophores, in biological samples obtained from time-resolved fluorescence microscopy. The contribution of this work is an algorithm, based on particle filter optimization, that solves the spectral unmixing problem for more than two fluorophores even when they present highly overlapping spectra at different wavelengths. The estimation of the proportional contributions of the elements in the sample is carried out by a Bayesianmethodology. Validation is done by using synthetic mixtures with two components and ex-vivo samples from human atherosclerotic tissue. © 2011 IEEE.

authors

• Arce Santana Edgar Román
• Campos Delgado Daniel Ulises
• Gutierrez-Navarro O.
• Jo J.A.
• Méndez García Martin Oswaldo

publication date

• 2011-01-01

published in

• CCE 2011 - 2011 8th International Conference on Electrical Engineering, Computing Science and Automatic Control, Program and Abstract Book  Proceedings

keywords

• Fluorescence Lifetime Imaging Microscopy (FLIM); in-vivo imaging; Lifetime Unmixing; Particle Filter; Time resolved fluorescence spectroscopy Fluorescence lifetime imaging microscopy; in-vivo imaging; Particle Filter; Time-resolved fluorescence spectroscopy; Unmixing; Automation; Control; Electrical engineering; Fluorescence; Fluorescence microscopy; Fluorescence spectroscopy; Nonlinear filtering; Process control; Tissue; Fluorophores

Digital Object Identifier (DOI)

• 10.1109/ICEEE.2011.6106604

start page

end page