In this article we propose an approach to improve the Monte Carlo simulation accuracy by implementing a full photon
path integration simulation in a non-voxelized complex three-dimensional heterogeneous model. Mouse body shape,
organs optical heterogeneities and fluorophore distribution are simulated by using boundary surface elements and basic
analytical shapes. In addition, external and internal surface roughness and refractive index mismatch for complex
angular objects are also considered and results are briefly compared with time sampled space voxelized Monte Carlo
code, in order to illustrate the impact of these improvements on the simulation results.
KEYWORDS: Luminescence, Monte Carlo methods, Diffusion, Tissues, Sensors, Computer simulations, Reflectivity, Biomedical optics, In vivo imaging, Light sources
The interest in fluorescence imaging has increased steadily in the last decade. Using fluorescence techniques, it is
feasible to visualize and quantify the function of genes and the expression of enzymes and proteins deep inside tissues.
When applied to small animal research, optical imaging based on fluorescent marker probes can provide valuable
information on the specificity and efficacy of drugs at reduced cost and with greater efficiency. Meanwhile,
fluorescence techniques represent an important class of optical methods being applied to in vitro and in vivo
biomedical diagnostics, towards noninvasive clinical applications, such as detecting and monitoring specific
pathological and physiological processes. ART has developed a time domain in vivo small animal fluorescence
imaging system, eXplore Optix. Using the measured time-resolved fluorescence signal, fluorophore location and
concentration can be quickly estimated. Furthermore, the 3D distribution of fluorophore can be obtained by
fluorescent diffusion tomography. To accurately analyze and interpret the measured fluorescent signals from tissue,
complex theoretical models and algorithms are employed. We present here a numerical simulator of eXplore Optix. It
generates virtual data under well-controlled conditions that enable us to test, verify, and improve our models and
algorithms piecewise separately. The theoretical frame of the simulator is an analytical solution of the fluorescence
diffusion equation. Compared to existing models, the coupling of fluorophores with finite volume size is taken into
consideration. Also, the influences of fluorescent inclusions to excitation and emission light are both accounted for.
The output results are compared to Monte-Carlo simulations.
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