Paper
28 April 2005 Float genetic algorithm for determination of particle size distribution and refractive index in polarized LSS
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Abstract
Polarized light scattering spectroscopy (LSS) is sensitive to the cell nuclear morphological changes in the various forms of epithelial dysplasia. Extensive studies illustrate it is a promising in situ technique to detect precancerous and early cancerous changes in the epithelial tissue. To determine the density and size distribution of cell nuclei with spectra, generally, Mie theory-based inverse model is adopted. This model is of multiple parameters, multiple extreme values and nonlinear. The determination of all unknown parameters needs to solve a nonlinear inverse problem. Other than least-square fitting used by previous studies, in this paper, we developed a novel method - float genetic algorithm (FGA) to determine the particle size distribution and refractive index for LSS. Our results showed that, relative errors of three estimated statistical quantities: diameter, standard deviation and refractive index are less than 5% for different additive Gauss noise levels with 70 iteration epochs. The errors gradually decrease with iteration epoch increases. Moreover, comparing with Newton-type iteration method coupled with a Marquardt-Tikhanov regularization scheme, FGA avoids the problems of local extreme value and selection of initial value and regularization parameters, thus obtains the advantages of high precision, stability and robustness.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yong Deng, Rui Hu, Qingming Luo, and Qiang Lu "Float genetic algorithm for determination of particle size distribution and refractive index in polarized LSS", Proc. SPIE 5693, Optical Tomography and Spectroscopy of Tissue VI, (28 April 2005); https://doi.org/10.1117/12.589583
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KEYWORDS
Refractive index

Particles

Genetic algorithms

Error analysis

Light scattering

Tissues

Mie scattering

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