3D optical sectioning with a new hyperspectral confocal fluorescence imaging system.

Nieman, Linda T. ; Sinclair, Michael B. ; Davidson, George S. ; Van Benthem, Mark Hilary ; Haaland, David Michael ; Timlin, Jerilyn Ann ; Sasaki, Darryl Yoshio ; Bachand, George David ; Jones, Howland D. T.

Sandia National Laboratories

关键词: Multivariate Analysis;    Fluorescence Spectroscopy.;    37 Inorganic, Organic, Physical And Analytical Chemistry;    Fluorescence;    59 Basic Biological Sciences;   

DOI  :  10.2172/902877
RP-ID  :  SAND2007-0399
RP-ID  :  AC04-94AL85000
RP-ID  :  902877

美国|英语

来源: UNT Digital Library

【 摘 要 】

A novel hyperspectral fluorescence microscope for high-resolution 3D optical sectioning of cells and other structures has been designed, constructed, and used to investigate a number of different problems. We have significantly extended new multivariate curve resolution (MCR) data analysis methods to deconvolve the hyperspectral image data and to rapidly extract quantitative 3D concentration distribution maps of all emitting species. The imaging system has many advantages over current confocal imaging systems including simultaneous monitoring of numerous highly overlapped fluorophores, immunity to autofluorescence or impurity fluorescence, enhanced sensitivity, and dramatically improved accuracy, reliability, and dynamic range. Efficient data compression in the spectral dimension has allowed personal computers to perform quantitative analysis of hyperspectral images of large size without loss of image quality. We have also developed and tested software to perform analysis of time resolved hyperspectral images using trilinear multivariate analysis methods. The new imaging system is an enabling technology for numerous applications including (1) 3D composition mapping analysis of multicomponent processes occurring during host-pathogen interactions, (2) monitoring microfluidic processes, (3) imaging of molecular motors and (4) understanding photosynthetic processes in wild type and mutant Synechocystis cyanobacteria.