CC BY
10B-I-18
BIOMEDICAL PHOTONICS
Unified Monte Carlo platform for light transport in complex geometries
M. Kirillin1, D. Kurakina1, I. Fiks1, A. Getmanskaya12, A. Gorshkov12, A. Khilov1, V. Perekatova1, V. Shishkova12, I. Turchin1, and E. Sergeeva1
1 - Institute of Applied Physics RAS, 46 Ulyanov St., Nizhny Novgorod, Russia, 603950 2 - N.I. Lobachevsky State University of Nizhny Novgorod, 23, Gagarin av., Nizhny Novgorod, Russia
Main author email address: mkirillin@yandex.ru
Development of novel optical imaging modalities and interpretation of the optical diagnostic data requires accurate models of light transport in biotissues, in many cases accounting for complex morphology of biological objects. Monte Carlo technique is a recognized gold standard methods for simulation of light transport in tissues benefiting from wide application areas, however, at the expense of computational time. In this paper we report on a unified Monte Carlo platform for simulation of light transport in complex geometries based on triangulation of the morphological structures boundaries. In contrast to traditional voxelization approach, such technique allows to accurately account for refraction of light beams on the boundaries, which is important in the case of low scattering inclusions, such as cerebral spinal fluid in the case of simulation of light transport in brain. The capabilities of the developed platform is demonstrated for murine head geometry (Fig.1a) extracted from the cryo-imaging data and for human skin geometry extracted from in vivo OCT-images. The murine head geometry was employed for simulations of fluorescence probing of a labeled inclusion in brain (Fig.1b-d). The segmentation of the diagnoistic data was performed based on routine machine learning techniques. The platform was also employed to evaluate probing depth in diffuse optical imaging modalities, such as optical diffuse spectroscopy (DOS) and fluorescence imaging (FI). Spectral dependencies of probing depth in DOS were acquired for different source-detector separations in the range of 1-8 mm. Simulations of fluorescence imaging allowed to develop an approach to detection of fluorophore localization based on sevral fluorescence excitation wavelengths.
(a) (b) (c) (d)
Fig.1. Complex geometry of murine head extracted from cryo-imaging (a); top (b), frontal (c) and side (d) views of the fluorescence emission from a labeled spherical inclusion in murine head.
The work was supported by Center of Excellence «Center of Photonics» funded by The Ministry of Science and Higher Education of the Russian Federation, contract № 075-15-2020-906.
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