A comparison of different phase scattering functions in modeling wave radiative transfer applied to the tissues with complex structures and dynamics

A. A. Isaeva; E. A. Isaeva; A. V. Pantyukov

doi:10.1117/12.2523212

3 June 2019 A comparison of different phase scattering functions in modeling wave radiative transfer applied to the tissues with complex structures and dynamics

A. A. Isaeva, E. A. Isaeva, A. V. Pantyukov

Author Affiliations +

Proceedings Volume 11066, Saratov Fall Meeting 2018: Laser Physics, Photonic Technologies, and Molecular Modeling; 110660X (2019) https://doi.org/10.1117/12.2523212
Event: International Symposium on Optics and Biophotonics VI: Saratov Fall Meeting 2018, 2018, Saratov, Russian Federation

Abstract

The results of the Monte Carlo radiative transfer modeling using scattering phase functions with the Henyey- Greenstein (HGPF) and the Gegenbauer kernel (GKPF) are presented. The Monte Carlo modeling of the light transport in the tissues with complex structures and dynamics is used as an original approach of speckle-correlometry based on the ring-like apertures and localized source of the probe light. The backscattering coefficient of the laser light scattered by the simulated medium was evaluated. The inhomogeneous layer, which contains a long inclusion with a different geometry and depth location for imitatng the blood vessel inside medium, was chosen as a simulated medium. The values of the scattering phase function with the Gegenbauer kernel are reduced to the values of the Henyey-Greenstein scattering phase function when the annular light detector has small radii, whereas for the annular big radii this transition is not carried out.

Citation Download Citation

A. A. Isaeva, E. A. Isaeva, and A. V. Pantyukov "A comparison of different phase scattering functions in modeling wave radiative transfer applied to the tissues with complex structures and dynamics", Proc. SPIE 11066, Saratov Fall Meeting 2018: Laser Physics, Photonic Technologies, and Molecular Modeling, 110660X (3 June 2019); https://doi.org/10.1117/12.2523212

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