Abstract

We present a method that is capable of extracting particle-size distribution (PSD) and concentration in heterogeneous turbid media by use of multispectral diffuse optical tomography (MSDOT). After the spectroscopic scattering images of the heterogeneous turbid media are obtained with MSDOT, the morphologic information of particles in the heterogeneities is recovered with an iterative regularized reconstruction algorithm based on Mie scattering theory when a particular form of PSD is assumed (Gaussian distribution is used in this study). The method described is tested and evaluated with both simulated and experimental data. The simulations are intended to test the sensitivity of the overall approach to noise effect. A series of phantom experiments are conducted with our newly developed ten-wavelength MSDOT system. Polystyrene microsphere suspensions contain particles of varying size from 2 to 6 μm as targets are embedded in a scattering background medium in these experiments. To achieve optimized results from experimental data, we developed a data preprocessing method for MSDOT as well as a scheme for calibrating scattering spectra. The results from both simulations and experiments show that the particle mean size and concentration can be reconstructed with acceptable accuracy, whereas the recovery of the standard deviation is sensitive to noise effect and can be as large as 86% from the experimental data.

© 2005 Optical Society of America

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