Photon Transport Model Research Articles

A combined analytical and Monte Carlo method for detailed simulations of antiscatter grids in x-ray medical imaging: implementing scatter within the grid

Objective. To implement a hybrid method, which combines analytical tracking and interaction simulation using Monte Carlo (MC) techniques, in order to model photon transport inside antiscatter grids (ASG) for x-ray imaging. Approach. A new tally was developed for PENELOPE (v.2018) and penEasy (v. 2020) MC code to simulate photon transmission through ASGs. Two established analytical algorithms from the literature were implemented in this tally. In addition, a new hybrid method was introduced by extending one of the analytical algorithms to include photon-interactions inside the grid, while preserving the imaged grid structure. Calculations of primary (TP), scatter (TS), and total (TT) grid transmissions in addition to the Q factor (Q = TP2/TT ) were performed. The new tally was validated for a quadric geometry ASG, and experimental measurements with a PMMA phantom of several thicknesses. In addition, the contribution of the scatter inside the grid was studied for three interspace materials, and a high resolution image of the grid was simulated. Main results. An excellent agreement was found between the two analytical models compared with the quadric grid without scatter, and the hybrid method with the geometrical grid with scatter. Average deviations of 0.2% and 1.4% were found between TP and TS for the hybrid method and quadric grid, while for the hybrid method and experimental measurements these values were 1% and 20%. Antiscatter grids with aluminium as interspace material had the highest amount of scatter from inside the grid to the final image, followed up by paper fibre and air. The high resolution image of the grid was equivalent using the quadric geometry or the hybrid mode. Significance. The hybrid method provides a means of studying scattered radiation from the antiscatter grid with the advantage of higher performance, with results that are consistent with a full quadric geometry simulation of the ASG.

Effects of the Earth curvature on Mie-scattering radiances at high solar-sensor geometries based on Monte Carlo simulations.

Given the importance of vector radiative transfer models in ocean color remote sensing and a lack of suitable models capable of analyzing the Earth curvature effects on Mie-scattering radiances, this study presents an enhanced vector radiative transfer model for a spherical shell atmosphere geometry by the Monte Carlo method (MC-SRTM), considering the effects of Earth curvature, different atmospheric conditions, flat sea surface reflectance, polarization, high solar and sensor geometries, altitudes and wavelengths. A Monte Carlo photon transport model was employed to simulate the vector radiative transfer processes and their effects on the top-of-atmosphere (TOA) radiances. The accuracy of the MC-SRTM was verified by comparing its scalar model outputs from Henyey-Greenstein (HG) phase function with the Kattawar-Adams model results, and the mean relative differences were less than 2.75% and 4.33% for asymmetry factors (g-values) of 0.5 and 0.7, respectively. The vector mode results of MC-SRTM for a spherical shell geometry with the Mie-scattering phase matrix were compared with the PCOART-SA model results (from Polarized Coupled Ocean-Atmosphere Radiative Transfer model based on the pseudo-spherical assumption), and the mean relative differences were less than 2.67% when solar zenith angles (SZAs) > 70 ∘ and sensor viewing zenith angles (VZAs) < 60 ∘ for two aerosol models (coastal and tropospheric models). Based on the MC-SRTM, the effects of Earth curvature on TOA radiances at high SZAs and VZAs were analyzed. For pure aerosol atmosphere, the effects of Earth curvature on TOA radiances reached up to 5.36% for SZAs > 70 ∘ and VZAs < 60 ∘ and reduced to less than 2.60% for SZAs < 70 ∘ and VZAs > 60 ∘. The maximum Earth curvature effect of pure aerosol atmosphere was nearly same (10.06%) as that of the ideal molecule atmosphere. The results also showed no statistically significant differences for the aerosol-molecule mixed and pure aerosol atmospheres. Our study demonstrates that there is a need to consider the Earth curvature effects in the atmospheric correction of satellite ocean color data at high solar and sensor geometries.

A singlet state oxygen generation model based on the Monte Carlo method of visible antibacterial blue light inactivation.

Visible antibacterial blue light (VABL) has received much attention recently as a nondestructive inactivation approach. However, due to the sparse distribution of bacteria, the light energy evaluation method used in existing studies is inaccurate. Thus, the sensitivity of microorganisms to VABL in different experiments cannot be compared. In this paper, a Monte Carlo-based photon transport model with the optimized scattering phase function was constructed. The model calculated the spatial light energy distribution and the temporal distribution of cumulative singlet state oxygen (CSO) under various cell and medium parameters. The simulation results show that when the cells are sparsely distributed, <30% of light energy from the light source is absorbed by microbes and participates in photochemical reactions. The CSO produced increases with cell density and cell size. Little light energy is available, and thus, the concentration of CSO produced is insufficient to inactivate microbes at deeper depths. As the light intensity and inactivation time increased, the production of singlet state oxygen tended to level off. The model proposed here can quantify the generation of singlet state oxygen and provide a more accurate light energy guide for the VABL inactivation process.

Assessing the Role of Photon Processes in Facilitating Radio Frequency Breakdown of Air at Atmospheric Pressure in Millimeter Gaps

The behavior of the breakdown electric field versus gap lengths (in the 1–5-mm range) and at different frequencies in the 1–80-MHz span, has been studied numerically at atmospheric pressure. Unlike previous studies of radio frequency (RF) breakdown, the role of photon-emission processes is explicitly included and shown to be important for large-area electrode configurations. Numerical analysis based on Monte Carlo calculations is used to predict the breakdown thresholds. The simulations embed a statistical photon transport model, based on random selections of emission angles and times from excited atoms, as well as photoemission from the electrodes. Simulation results compare well with experimental data from our group, but only with the inclusion of photon processes. Though both photoemission and photoionization are included in the breakdown physics, the former is identified as the dominant process. The frequency behavior of breakdown fields is also assessed with the inclusion of photons, and the results reveal a U-shaped trend with increasing values for smaller gaps.

Computational scatter correction in near real-time with a fast Monte Carlo photon transport model for high-resolution flat-panel CT

In computed tomography (CT), scattering causes server quality degradation of the reconstructed CT images by introducing streaks and cupping artifacts which reduce the detectability of low contrast objects. Monte Carlo (MC) simulation is considered the most accurate approach for scatter estimation. However, the existing MC estimators are computationally expensive, especially for high-resolution flat-panel CT. In this paper, we propose a fast and accurate MC photon transport model which describes the physics within the 1 keV to 1 MeV range using multiple controllable key parameters. Based on this model, scatter computation for a single projection can be completed within a range of a few seconds under well-defined model parameters. Smoothing and interpolation are performed on the estimated scatter to accelerate the scatter calculation without compromising accuracy too much compared to measured near scatter-free projection images. Combining the fast scatter estimation with the filtered backprojection (FBP), scatter correction is performed effectively in an iterative manner. To evaluate the proposed MC model, we have conducted extensive experiments on the simulated data and real-world high-resolution flat-panel CT. Compared to the state-of-the-art MC simulators, the proposed MC model achieved a 15times acceleration on a single-GPU compared to the GPU implementation of the Penelope simulator (MCGPU) utilizing several acceleration techniques, and a 202 times speed-up on a multi-GPU system compared to the multi-threaded state-of-the-art EGSnrc MC simulator. Furthermore, it is shown that for high-resolution images, scatter correction with sufficient accuracy is accomplished within one to three iterations using a FBP and the proposed fast MC photon transport model.

Monte Carlo method for assessment of a multimodal insertable biosensor.

.Significance: Continuous glucose monitors (CGMs) are increasingly utilized as a way to provide healthcare to the over 10% of Americans that have diabetes. Fully insertable and optically transduced biosensors are poised to further improve CGMs by extending the device lifetime and reducing cost. However, optical modeling of light propagation in tissue is necessary to ascertain device performance.Aim: Monte Carlo modeling of photon transport through tissue was used to assess the luminescent output of a fully insertable glucose biosensor that uses a multimodal Förster resonance energy transfer competitive binding assay and a phosphorescence lifetime decay enzymatic assay.Approach: A Monte Carlo simulation framework of biosensor luminescence and tissue autofluorescence was built using MCmatlab. Simulations were first validated against previous research and then applied to predict the response of a biosensor in development.Results: Our results suggest that a diode within the safety standards for light illumination on the skin, with far-red excitation, allows the luminescent biosensor to yield emission strong enough to be detectable by a common photodiode.Conclusions: The computational model showed that the expected fluorescent power output of a near-infrared light actuated barcode was five orders of magnitude greater than a visible spectrum excited counterpart biosensor.

A new optical photon transport model for application to high aspect ratio scintillation pillars

A new Monte Carlo model of optical photon transport has been developed for application to scintillation pillars with side surfaces modeled using their measured 3D topography. The model addresses deficiencies of existing models specifically pertinent to high aspect ratio scintillator geometries. Inaccuracies with these models’ description of the reflectance of scintillation photons at media boundaries are exacerbated by the high number of surface interactions in such geometries. These models rely either on (a) user-specified parameters that are challenging to set, or (b) pre-computed look-up tables that assume geometrically unconstrained photon incidence on uniform surface finishes, an assumption that is invalid in high aspect ratio geometries. Alternatively, the new model reconstructs the side surfaces of a pillar from 3D topographic measurements and uses first-principles physics of reflection and transmission to transport photons over the surfaces’ microscopic features and throughout the entire pillar volume. It takes advantage of the recent availability of open-source software capable of complex surface modeling and ray-tracing, as well as high performance computing. The model was validated against measurements of the number of photoelectrons (PEs) generated in two silicon photomultipliers (SiPMs) located at the ends of 5 mm × 5 mm × 200 mm EJ-204 scintillation pillars with different surface finishes. It was also validated against the relative amplitudes and arrival time difference of the SiPMs’ signals. The model accurately predicts the measurements as function of the scintillation position along the pillars’ length with 2% mean-absolute-percentage error (MAPE) in the number of PEs, and 16% in the relative amplitudes. The root-mean-squared error (RMSE) in the arrival time difference is 0.114 ns. The model also predicts the experimentally observed higher scintillation light collection in pillars with smoother side surfaces. A proof-of-concept code of the model is available as open source.

Multispectral snapshot imaging of skin microcirculatory hemoglobin oxygen saturation using artificial neural networks trained on in vivo data.

.SignificanceDeveloping algorithms for estimating blood oxygenation from snapshot multispectral imaging (MSI) data is challenging due to the complexity of sensor characteristics and photon transport modeling in tissue. We circumvent this using a method where artificial neural networks (ANNs) are trained on in vivo MSI data with target values from a point-measuring reference method.AimTo develop and evaluate a methodology where a snapshot filter mosaic camera is utilized for imaging skin hemoglobin oxygen saturation (), using ANNs.ApproachMSI data were acquired during occlusion provocations. ANNs were trained to estimate with MSI data as input, targeting data from a validated probe-based reference system. Performance of ANNs with different properties and training data sets was compared.ResultsThe method enables spatially resolved estimation of skin tissue . Results are comparable to those acquired using a Monte-Carlo-based approach when relevant training data are used.ConclusionsTraining an ANN on in vivo MSI data covering a wide range of target values acquired during an occlusion protocol enable real-time estimation of maps. Data from the probe-based reference system can be used as target despite differences in sampling depth and measurement position.

Scatter Correction and Contrast Improvement of Concrete Objects Using Monte Carlo Method

Estimating the load-carrying capacity of concrete structures is a major challenge as the infrastructure industry thrives to reduce the consumption of concrete for environmental concerns as well as improving the cost and time efficiency of infrastructural projects. Quantifying such load-carrying capacity needs a detailed study of the micro-structures of the concrete mixture composed of stones, reinforcement, and cement matrix. Computed Tomography (CT) provides a reliable nondestructive technique to analyze and segment the different materials within the concrete structures. However, CT is normally accompanied by different kinds of artifacts that highly degrades the quality of the reconstructed image. Among these artifacts, scatter imposes severe degradation of the quality of the image including reduced contrast between different materials, cupping and streaks artifacts. Several methods were used to remove the scatter effect. The most effective way to correct for the scatter effect is by the use of the Monte Carlo (MC) method due to the accurate modeling of the physics accompanying the photon matter interaction. In this work, a fast MC photon transport model accelerated over the use of the GPU(s) platforms is developed. It is extensively verified against several well-known simulators and experimentally has been used to correct the scatter effect and to improve the contrast between the concrete component.

A hierarchical Bayesian model for background variation in radiation source localization

In this paper, we apply a new model to account for varying background radiation in radiological source localization. We present a hierarchical Bayesian model that simultaneously infers background and source location parameters without requiring separate estimation of the background radiation at each detector location. We employ a simplified photon transport model to reduce the computational expense of Bayesian model calibration. We demonstrate the model accuracy by localizing a cesium-137 source in a simulated city block, and we analyze experimental field measurements with varying background. In both cases, the model provides sufficient fidelity that we can locate the source while simultaneously estimating background radiation.

Effect of purification, dehydration, and coagulation processes on the optical parameters of biological tissues

In this study, the effects of purification, dehydration, and coagulation processes on the absorption and reduced scattering coefficients of chicken liver tissues have been investigated by using a single integrating sphere system. The purification process performed on the tissue samples to remove blood residue has been found to cause a slight change in the optical parameters. Although the dehydration process brings about an increase in the absorption coefficient due to the water loss, no direct relationship has been observed between the reduced scattering coefficient and the dehydration level of the tissue. In addition, it has been observed that there was a relatively small increase in the absorption coefficient and a significant increase in the reduced scattering coefficient after the coagulation process. Therefore, it can be said that the optical penetration depth decreased significantly after dehydration and coagulation processes unlike blood purification. Moreover, fluence rate distributions inside the fresh, blood purified, dehydrated, and coagulated tissue models have been investigated by using the Monte Carlo modeling of photon transport in multilayered tissues simulation code.

Малоразмерный черенковский телескоп с полупроводниковыми фотодетекторами: полночастичное моделирование порога регистрации космических гамма-источников

Full-particle modeling of gamma-ray and proton induced extensive air showers (EASs) in the Earth's atmosphere as well as Monte Carlo modeling of photon transport in a small size Cherenkov telescope and signal registration with its camera based on the OnSemi MicroFJ SiPM detectors have been performed. Calculations have been carried out for primaries within the 0.3 - 30 TeV range and a telescope with a 10 m(2) mirror similar to the unit employed at the TAIGA observatory. It has been shown that even with strict selection criteria aimed at high quality EAS images, the threshold detection energy of the SiPM-based camera would not exceed 0.8 TeV - about twice as low as the current threshold of the TAIGA-IACT camera based on vacuum photomultipliers.

Hybrid mesh and voxel based Monte Carlo algorithm for accurate and efficient photon transport modeling in complex bio-tissues

Over the past decade, an increasing body of evidence has suggested that three-dimensional (3-D) Monte Carlo (MC) light transport simulations are affected by the inherent limitations and errors of voxel-based domain boundaries. In this work, we specifically address this challenge using a hybrid MC algorithm, namely split-voxel MC or SVMC, that combines both mesh and voxel domain information to greatly improve MC simulation accuracy while remaining highly flexible and efficient in parallel hardware, such as graphics processing units (GPU). We achieve this by applying a marching-cubes algorithm to a pre-segmented domain to extract and encode sub-voxel information of curved surfaces, which is then used to inform ray-tracing computation within boundary voxels. This preservation of curved boundaries in a voxel data structure demonstrates significantly improved accuracy in several benchmarks, including a human brain atlas. The accuracy of the SVMC algorithm is comparable to that of mesh-based MC (MMC), but runs 2x-6x faster and requires only a lightweight preprocessing step. The proposed algorithm has been implemented in our open-source software and is freely available at http://mcx.space.

Exploiting scale-invariance: a top layer targeted inverse model for hyperspectral images of wounds.

Detection of re-epithelialization in wound healing is important, but challenging. Hyperspectral imaging can be used for non-destructive characterization, but efficient techniques are needed to extract and interpret the information. An inverse photon transport model suitable for characterization of re-epithelialization is validated and explored in this study. It exploits scale-invariance to enable fitting of the epidermal skin layer only. Monte Carlo simulations indicate that the fitted layer transmittance and reflectance spectra are unique, and that there exists an infinite number of coupled parameter solutions. The method is used to explain the optical behavior of and detect re-epithelialization in an in vitro wound model.

Parallelized Monte Carlo Photon Transport Simulations for Arbitrary Multi-Angle Wide-Field Illumination in Optoacoustic Imaging

Optoacoustic imaging (OAI) or photoacoustic imaging can resolve the distribution of tissue chromophores and optical contrast agents deep inside tissue from the optoacoustic detection with multi-spectral illumination. The development of a fast and accurate modeling method for the photon transport in OAI is necessary to quantitatively evaluate the tissue optical parameters. This paper presents a parallelized Monte Carlo modeling method especially for OAI (MCOAI) to simulate photon transport in bio-tissues with arbitrary multi-angle wide-field illumination. The performance of the MCOAI method is verified by comparison with the graphics processing unit (GPU)-accelerated MCX method in the typical cases with the pencil beam and ring source illumination. The simulation results demonstrate the GPU-based MCOAI method has equivalent accuracy and significantly improved computation efficiency, compared to the MCX method. The simulations with cylindrical and hemispherical source illumination further illustrate that the MCOAI method can effectively implement three-dimensional photon transport simulation for typical illumination geometries of OAI systems. A cross-section of Digimouse is selected as a realistic heterogeneous phantom illuminated with six different light sources usually employed in OAI, in order to prove the necessity of establishing photon transport modeling in OAI for the quantitative visualization in deep tissues. The MCOAI method can provide a powerful tool to efficiently establish photon transport modeling with arbitrary illumination modes for OAI applications.

Photon transport model for dense polydisperse colloidal suspensions using the radiative transfer equation combined with the dependent scattering theory.

In near-infrared imaging and spectroscopy, high-fidelity modeling of photon transport for dense polydisperse colloidal suspensions is crucial. We developed photon transport models using the radiative transfer equation (RTE) with the dependent scattering theory (DST) at volume fractions up to 20%. The polydispersity and interference effects strongly influence results of the scattering properties and the RTE in cases of small mean diameter and large variance of the particle size distribution. We compared the RTE-results for the Henyey-Greenstein (conventional) function with those for the phase function using the DST. The RTE-results differ between both functions at low volume fractions for forward scattering media, suggesting the limitation of the conventional function.

Hyperspectral characterization of re-epithelialization in an in vitro wound model.

In vitro wound models are useful for research on wound re-epithelialization. Hyperspectral imaging represents a non-destructive alternative to histology analysis for detection of re-epithelialization. This study aims to characterize the main optical behavior of a wound model in order to enable development of detection algorithms. K-Means clustering and agglomerative analysis were used to group spatial regions based on the spectral behavior, and an inverse photon transport model was used to explain differences in optical properties. Six samples of the wound model were prepared from human tissue and followed over 22 days. Re-epithelialization occurred at a mean rate of 0.24 mm2 /day after day 8 to 10. Suppression of wound spectral features was the main feature characterizing re-epithelialized and intact tissue. Modeling the photon transport through a diffuse layer placed on top of wound tissue properties reproduced the spectral behavior. The missing top layer represented by wounds is thus optically detectable using hyperspectral imaging.

A Framework for Efficient Calculation of Photoionization and Photodetachment Rates With Application to the Lower Ionosphere

AbstractA framework is developed to model photoionization of metals deposited in the lower ionosphere as a result of meteoric ablation and photodetachment of electrons from negative ions of the Earth's ionosphere due to sources of emission other than solar radiation. A wide range of the electromagnetic spectrum including cases of negligible, moderate, and significant absorption of radiation is considered. We limit our scope to the radiation transport through lower ionospheric regions, in case when molecular oxygen, O2, is considered as the main absorber of radiation as photoabsorption due to ozone is only effective at stratospheric altitudes and molecular nitrogen, N2, is transparent to radiation with wavelengths longer than ∼100 nm. We model photon transport in an exponential atmosphere and derive efficient differential representations of the problem in case of negligible photoabsorption and constant pressure approximations. Photoabsorption asymmetry in the atmosphere is demonstrated in case of photons with absorption scales comparable to the scale height of the atmosphere. The application of the model to photoionization in the lower ionosphere is demonstrated by considering photoionization of meteoric species due to photons of the Lyman‐Birge‐Hopfield (LBH) band system of N2 observed in the aurora and in the lightning‐induced transient luminous events. Furthermore, we model detachment of electrons from negative ions of the ionosphere due to the first positive and the second positive band systems of N2, and the first negative band system of N , also observed in the sources mentioned above.

Prediction of tissue optical properties using the Monte Carlo modeling of photon transport in turbid media and integrating spheres

Monte Carlo methods are an established technique for simulating light transport in biological tissue. Integrating spheres make experimental measurements of the reflectance and transmittance of a sample straightforward and inexpensive. This work presents an extension to existing Monte Carlo photon transport methods to simulate integrating sphere experiments. Crosstalk between spheres in dual-sphere experiments is accounted for in the method. Analytical models, previous works on Monte Carlo photon transport, and experimental measurements of a synthetic tissue phantom validate this method. We present two approaches for using this method to back-calculate the optical properties of samples. Experimental and simulation uncertainties are propagated through both methods. Both back-calculation methods find the optical properties of a sample accurately and precisely. Our model is implemented in standard Python 3 and CUDA C++ [J. Nickolls, I. Buck, M. Garland, and K. Skadron, ACM Queue 6, 40 (2008)] and is publicly available in Code 1.

Scattering Correction of CBCT Projections for the Quality Enhanced CT Reconstruction Using an Efficient Monte Carlo Photon Transport Model

In industrial computed tomography, cone beam computed tomography (CBCT) setups are state-of-art because of its capabilities and speed. However, this technique highly suffers from the effect of scatter in comparison to fan beam computed tomography due to the large scanning 2D field of view. CBCT is more preferable to be used since it is considerably faster. In this work a fast Monte Carlo forward projection model based on photon transport has been developed to subtract the scatter from the measured X-ray projections. The ability of this forward model to compute any complex object from CAD models based on meshes polyhedron validate the proposed scatter subtraction algorithm. Depending on the number of photons used, the complexity and the size of the object each X-ray projection is obtained within two minute or less with this model. In addition to the use of the variance reduction techniques for a fast calculation of the scatter, the proposed scatter subtraction algorithm has been further reduced in computation time by the use of smoothing filters, mainly by the use of Savitzky-Golay filter which is a type of a squares polynomial approximation filter, this kind of smoothing plays significant role in the reduction of the computations time.