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Proceedings Paper

Fluorescence optical tomography using independent component analysis to detect small targets in turbid media
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Paper Abstract

A new approach for optical fluorescence tomographic imaging of targets in a turbid medium that uses the independent component analysis (ICA) from information theory is presented. Fluorescence signals from targets embedded in a turbid medium are measured on the boundary of the medium using a multi-source excitation and a multi-detector acquisition scheme. Differences between excitation and fluorescence wavelengths enable sensitive, minimal-background signal acquisition. ICA of the fluorescence signal on the medium boundary sorts out the embedded ob-jects, and their locations are obtained from Green’s function analysis based on any appropriate light propagation model. Fluorescence tomographic imaging experiments were carried out using Intralipid-10% suspension in water contained in a 50-mm thick rectangular transparent plastic cell as the turbid medium, and small glass spheres containing indocyanine green (ICG) solution as fluorescent targets. The near-infrared (NIR) fluorescence was excited using 785 nm light, and monitored over a narrow band around 830 nm. The transport mean free paths at 785 nm and 830 nm were 1.01 mm and 1.14 mm, respectively. The approach could image and determine the position of an ICG filled sphere of radius as small as 4 mm. It is applicable to small objects, different medium geometries, and amenable to near real time imaging applications.

Paper Details

Date Published: 28 April 2005
PDF: 4 pages
Proc. SPIE 5693, Optical Tomography and Spectroscopy of Tissue VI, (28 April 2005); doi: 10.1117/12.591961
Show Author Affiliations
M. Alrubaiee, CUNY/City College of New York (United States)
M. Xu, CUNY/City College of New York (United States)
S, K. Gayen, CUNY/City College of New York (United States)
R. R. Alfano, CUNY/City College of New York (United States)


Published in SPIE Proceedings Vol. 5693:
Optical Tomography and Spectroscopy of Tissue VI
Britton Chance; Robert R. Alfano; Bruce J. Tromberg; Mamoru Tamura; Eva M. Sevick-Muraca, Editor(s)

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