Abstract
Spatial frequency domain imaging (SFDI) utilizes the projection of spatially modulated light patterns upon biological tissues to obtain optical property maps for absorption and reduced scattering. Conventionally, both forward modeling and optical property recovery are performed using pixel-independent models, calculated via analytical solutions or Monte-Carlo-based look-up tables, both assuming a homogenous medium. The resulting recovered maps are limited for samples of high heterogeneity, where the homogenous assumption is not valid. NIRFAST, a FEM-based image modeling and reconstruction tool, simulates complex heterogeneous tissue optical interactions for single and multiwavelength systems. Based on the diffusion equation, NIRFAST has been adapted to perform pixel-dependent forward modeling for SFDI. Validation is performed within the spatially resolved domain, along with homogenous structured illumination simulations, with a recovery error of <2%. Heterogeneity is introduced through cylindrical anomalies, varying size, depth and optical property values, with recovery errors of <10%, as observed across a variety of simulations. This work demonstrates the importance of pixel-dependent light interaction modeling for SFDI and its role in quantitative accuracy. Here, a full raw image SFDI modeling tool is presented for heterogeneous samples, providing a mechanism towards a pixel-dependent SFDI image modeling and parameter recovery system.
Highlights
Spatial frequency domain imaging (SFDI) is an optical imaging technique in which visible-NIR light is projected onto a region of interest in the form of spatial modulated light projections
The first step is to consider a simple SRS model using the NIRFAST semi-infinite analytical model, validated against an existing analytical solution from virtual photonics (VP). This validation data is derived from the virtual photonics modeling software (Irvine, CA, USA), in which the reflectance at a given distance, R(ρ), from a single isotropic point source located at a depth of l∗, the transport mean-free path is: l∗ =
The use of a NIRFAST SFDI forward model allows for the simulation of arbitrary shaped models, along with both complex geometries and varying optical properties
Summary
Spatial frequency domain imaging (SFDI) is an optical imaging technique in which visible-NIR light is projected onto a region of interest in the form of spatial modulated light projections. The backscattered diffuse light is processed to obtain the reflectance spectrum for both the range of wavelengths and spatial frequencies imaged, before inverse modeling is utilized to obtain maps of absorption and reduced scattering parameters These maps are obtained following a simple three-step analysis procedure, in which the diffuse reflectance images are demodulated and calibrated, before optical fitting using inverse modeling and minimization algorithms. This modeling is performed using either approximated analytical solutions to the diffusion equation or through a variety of Monte-Carlo-based simulations and look-up tables [1]. A limited number of commercial SFDI systems are currently available (Modulim, Irvine, CA, USA), whilst recent research has shown an open-hardware model, with a simple benchtop SFDI, which is available with full setup and usage instructions from
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