Distribution Of Absorption Coefficient Research Articles

Extractor-attention-predictor network for quantitative photoacoustic tomography

Quantitative photoacoustic tomography (qPAT) holds great potential in estimating chromophore concentrations, whereas the involved optical inverse problem, aiming to recover absorption coefficient distributions from photoacoustic images, remains challenging. To address this problem, we propose an extractor-attention-predictor network architecture (EAPNet), which employs a contracting–expanding structure to capture contextual information alongside a multilayer perceptron to enhance nonlinear modeling capability. A spatial attention module is introduced to facilitate the utilization of important information. We also use a balanced loss function to prevent network parameter updates from being biased towards specific regions. Our method obtains satisfactory quantitative metrics in simulated and real-world validations. Moreover, it demonstrates superior robustness to target properties and yields reliable results for targets with small size, deep location, or relatively low absorption intensity, indicating its broader applicability. The EAPNet, compared to the conventional UNet, exhibits improved efficiency, which significantly enhances performance while maintaining similar network size and computational complexity.

Flame soot absorption coefficient and temperature reconstruction through line-of-sight attenuation and light field imaging

The accuracy and efficiency of 3-D flame temperature field reconstruction using the light field imaging technique heavily depend on soot radiation characteristics. In this study, we employ the line-of-sight attenuation method to reconstruct the soot absorption coefficient distribution in a pure absorbing flame. Utilizing these soot absorption coefficients, the radiative transfer equation is effectively transformed within the framework of the light field imaging technique into a linear inverse problem and also outlines the flame boundary. This proposed strategy reduces the unwanted detection rays significantly, thus eliminating the extensive computational processing. Consequently, the proposed approach substantially enhances the accuracy and efficiency of flame temperature reconstruction. Numerical simulations were carried out on a bimodal asymmetric flame to validate the noise tolerance capabilities, investigate the effects of varying voxel numbers on flame division and carry out a comparative study. Experimental studies were also conducted to reconstruct flame temperature and soot absorption coefficient distributions under different combustion operating conditions. Thermocouple measurements were performed and compared with the reconstructed temperatures. Outcomes achieved from both numerical simulations and experimental studies demonstrate the feasibility, accuracy and robustness of the proposed method.

Enhanced model iteration algorithm with graph neural network for diffuse optical tomography.

Diffuse optical tomography (DOT) employs near-infrared light to reveal the optical parameters of biological tissues. Due to the strong scattering of photons in tissues and the limited surface measurements, DOT reconstruction is severely ill-posed. The Levenberg-Marquardt (LM) is a popular iteration method for DOT, however, it is computationally expensive and its reconstruction accuracy needs improvement. In this study, we propose a neural model based iteration algorithm which combines the graph neural network with Levenberg-Marquardt (GNNLM), which utilizes a graph data structure to represent the finite element mesh. In order to verify the performance of the graph neural network, two GNN variants, namely graph convolutional neural network (GCN) and graph attention neural network (GAT) were employed in the experiments. The results showed that GCNLM performs best in the simulation experiments within the training data distribution. However, GATLM exhibits superior performance in the simulation experiments outside the training data distribution and real experiments with breast-like phantoms. It demonstrated that the GATLM trained with simulation data can generalize well to situations outside the training data distribution without transfer training. This offers the possibility to provide more accurate absorption coefficient distributions in clinical practice.

Stochastic modeling of porous sound absorbing materials using homogenization method and machine learning

This research introduces a novel approach to investigate porous sound absorbing materials using stochastic modeling techniques. The study employs the homogenization method and machine learning to predict the acoustic properties of porous materials. The homogenization method simplifies the analysis of microstructural properties in porous materials, while machine learning is a data analysis technique that utilizes algorithms to learn from data and make predictions. By integrating these methods, this study quantitatively assesses the impact of microscopic structural randomness on sound absorption properties. The study assumes that microstructural parameters are random variables and calculates the sound absorption coefficient through homogenization method. This dataset serves as input for machine learning. A Gaussian process regression model is developed using the dataset to evaluate the distribution of the sound absorption coefficient via the Gauss-Hermite quadrature method. The study implements Bayesian optimization, utilizing the variance of the resulting probability distribution as the acquisition function, to adaptively update the dataset. By iteratively performing these processes, the probability distribution of the sound absorption coefficient can be predicted efficiently and with high accuracy.

The Optical Inverse Problem in Quantitative Photoacoustic Tomography: A Review

Photoacoustic tomography is a fast-growing biomedical imaging modality that combines rich optical contrast with a high acoustic resolution, at depths in tissues. Building upon the foundation of this technique, novel quantitative photoacoustic tomography fully leverages its advantages while further delivering improved quantification capabilities to produce high-accuracy concentration estimates, which has attracted substantial research interest in recent years. The kernel challenge associated with quantitative photoacoustic tomography is an optical inverse problem aiming to recover the absorption coefficient distribution from the conventional photoacoustic image. Although the crucial importance of the optical inversion has been widely acknowledged, achieving it has remained a persistent challenge due to the inherent non-linearity and non-uniqueness. In the past decade, numerous methods were proposed and have made noticeable progress in addressing this concern. Nevertheless, a review has been conspicuously absent for a long time. Aiming to bridge this gap, the present study comprehensively investigates the recent research in this field, and methods identified with significant value are introduced in this paper. Moreover, all included methods are systematically classified based on their underlying principles. Finally, we summarize each category and highlight its remaining challenges and potential future research directions.

On-Line Fluorescence Microscopy for Identification and Imaging of Apoptotic Cell with Synchrotron-Based Soft X-ray Tomography.

Synchrotron-based soft X-ray tomography (SXT), providing three-dimensional morphology and quantitative distribution of linear absorption coefficient (LAC) of the imaged objects, is widely used in many fields to obtain ultra-structure images, especially in cellular imaging. Off-line fluorescence microscopies (FMs) are combined to identify the type of organelles and status of cells. However, deformation and displacement usually occur during the transfer and loading process, which decreases the precision of two-modal images' registration. In this paper, we report on an on-line FM, at the SXT station (BL07W) of the National Synchrotron Radiation Laboratory (NSRL), which avoids deformation and displacement. Therefore, researchers can easily find the sample and take the useful data without tedious post-processing. Combining SXT with on-line FM, we achieved the identification and high-resolution imaging of an apoptotic cell. The experiments revealed that the LAC of the nucleus of the apoptotic cell was larger than that of a normal cell, which could be explained by nucleus pyknosis of the apoptotic cell.

Reconstruction of fluorophore absorption and fluorescence lifetime using early photon mesoscopic fluorescence molecular tomography: a phantom study.

Fluorescence molecular lifetime tomography (FMLT) plays an increasingly important role in experimental oncology. The article presents and experimentally verifies an original method of mesoscopic time domain FMLT, based on an asymptotic approximation to the fluorescence source function, which is valid for early arriving photons. The aim was to justify the efficiency of the method by experimental scanning and reconstruction of a phantom with a fluorophore. The experimental facility included the TCSPC system, the pulsed supercontinuum Fianium laser, and a three-channel fiber probe. Phantom scanning was done in mesoscopic regime for three-dimensional (3D) reflectance geometry. The sensitivity functions were simulated with a Monte Carlo method. A compressed-sensing-like reconstruction algorithm was used to solve the inverse problem for the fluorescence parameter distribution function, which included the fluorophore absorption coefficient and fluorescence lifetime distributions. The distributions were separated directly in the time domain with the QR-factorization least square method. 3D tomograms of fluorescence parameters were obtained and analyzed using two strategies for the formation of measurement data arrays and sensitivity matrices. An algorithm is developed for the flexible choice of optimal strategy in view of attaining better reconstruction quality. Variants on how to improve the method are proposed, specifically, through stepped extraction and further use of a posteriori information about the object. Even if measurement data are limited, the proposed method is capable of giving adequate reconstructions but their quality depends on available a priori (or a posteriori) information. Further research aims to improve the method by implementing the variants proposed.

Optical simulation and design of high-absorption thin-film perovskite halide solar cells based on embedded quadrilateral cluster nanoparticles

Recently, thin-film organic–inorganic hybrid perovskite solar cells have a high efficiency-to-cost ratio. However, due to the thickness of the absorber layer, photon management in the absorber layer is still not optimized. This research suggests an embedded side for the plasmonic perovskite solar cells. Using Maxwell equations solver (finite-difference time-domain method), numerical optimization of photocurrent for gold, copper, silver, and aluminum cluster of nanoparticles in different geometries including quadrilateral, hexagonal, octagonal, and dodecagonal was investigated at a wavelength range from 300 nm to 800 nm. Moreover, the basic factors of optical simulation such as absorption coefficient, generation rate, and electric field distribution are shown in the optimal case, and the important parasitic absorption challenge for the cluster of nanoparticles was considered in the calculation of the net absorption. The reference cell uses a perovskite absorber (CH3NH3PbI3) with a thickness of 250 nm, which can significantly reduce the amount of lead, and the solar cell's toxicity. The photocurrent density for the optimized case utilizing spherical cluster of nanoparticles is obtained 21.74mAcm−2, which is enhanced by approximately 25.6% compared to perovskite solar cells without nanoparticles. Finally, the best-case cluster nanoparticle is coated with an ultra-thin-film SiO2 layer, to help the chemical and thermal stability of metallic nanoparticles in the photoactive region. According to the final proposed model, the photocurrent of 22.28mAcm−2 and enhancement of 28.72% were obtained. Besides, the proposed solar cell's open-circuit voltage, fill factor, and conversion efficiency are calculated at around 1.003 V, 0.88, and 19.71%, respectively.

Why the Forcing from Carbon Dioxide Scales as the Logarithm of Its Concentration

Abstract The radiative forcing from carbon dioxide is approximately logarithmic in its concentration, producing about 4 W m−2 of global-mean forcing for each doubling. Although these are basic facts of climate science, competing explanations for them have been given in the literature. Here, the reasons for the logarithmic forcing of carbon dioxide are explored in detail and a simplified model for the forcing is constructed. An essential component is the particular distribution of absorption coefficients within the 15-μm band of carbon dioxide. An alternative explanation, which does not depend on the spectrum of carbon dioxide but instead hinges on the tropospheric lapse rate, is shown to be neither necessary nor sufficient to explain the logarithmic forcing of carbon dioxide and to be generally inapplicable to well-mixed greenhouse gases in Earth’s atmosphere.

Quantitative endoscopic photoacoustic tomography using a convolutional neural network.

Endoscopic photoacoustic tomography (EPAT) is a catheter-based hybrid imaging modality capable of providing structural and functional information of biological luminal structures, such as coronary arterial vessels and the digestive tract. The recovery of the optical properties of the imaged tissue from acoustic measurements achieved by optical inversion is essential for implementing quantitative EPAT (qEPAT). In this paper, a convolutional neural network (CNN) based on deep gradient descent is developed for qEPAT. The network enables the reconstruction of images representing the spatially varying absorption coefficient in cross-sections of the tubular structures from limited measurement data. The forward operator reflecting the mapping from the absorption coefficient to the optical deposition due to pulsed irradiation is embedded into the network training. The network parameters are optimized layer by layer through the deep gradient descent mechanism using the numerically simulated data. The operation processes of the forward operator and its adjoint operator are separated from the network training. The trained network outputs an image representing the distribution of absorption coefficients by inputting an image that represents the optical deposition. The method has been tested with computer-generated phantoms mimicking coronary arterial vessels containing various tissue types. Results suggest that the structural similarity of the images reconstructed by our method is increased by about 10% in comparison with the non-learning method based on error minimization in the case of the same measuring view.

Image quality improvements of diffuse optical tomography by using multiple polarization components

The inverse process of diffuse optical tomography (DOT) is ill-posed, which has a significant effect on the quality of the reconstructed results. In this paper, the polarization characteristics of light are introduced into the inverse solution model of DOT to increase the solution constraints and improve the imaging quality. The spectral element method is used to numerically solve the vector radiative transfer equation, which is used to simulate the propagation of polarized light in a scattering medium. The DOT reverse solution algorithm based on the polarization component is constructed so that the Stokes vector can be used for absorption coefficient and scattering coefficient reconstruction. The simulation and experimental results show that when polarized light is used for incidence, using the intensity component and the multi-polarization component to solve the DOT inverse model can improve the reconstruction accuracy of the medium absorption coefficient distribution and the DOT image quality.

Assessing the UV-pulse-laser-induced damage density of fused silica optics using photo-thermal absorption distribution probability curves.

A photo-thermal absorption distribution probability curve based on a normal distribution model was proposed to describe the distribution of absorptive defects on fused silica surfaces under different processing conditions. Simultaneously, the maximum distribution probability absorption coefficient (MPA) and absorption distribution deviation (ADD) were used to quantitatively describe the overall absorption level and the uniformity of the absorption distribution on the fused silica surface. Based on this, the MPA (μ) and ADD (δ) were used to establish a statistical numerical relationship with the surface damage density of fused silica. The results showed that when μ ≤ 0.095 ± 0.015 and δ ≤ 0.045 ppm, the fused silica optics met the manufacturing process requirements for high laser-induced damage performance. Thus, a non-destructive approximate evaluation of the laser-induced damage density on the fused silica surface was achieved. This evaluation method provides a new, to the best of our knowledge, technology for evaluating the manufacturing process quality related to the damage performance of fused silica optics in high-power solid-state laser facilities and is an important supplement to popular destructive laser-induced damage testing methods.

Dynamics of Nutrients and Colored Dissolved Organic Matter Absorption in a Wetland-Influenced Subarctic Coastal Region of Northeastern Japan: Contributions From Mariculture and Eelgrass Meadows

Coastal oceans interacting with terrestrial ecosystems play an important role in biogeochemical cycles. It is therefore essential to research land–ocean interactions for further understanding of the processes influencing nutrients dynamics in coastal areas. We investigated the seasonal and spatial distribution of nutrient concentrations and light absorption coefficients of colored dissolved organic matter (CDOM), non-algal particles (NAP), and phytoplankton in a wetland-influenced river–eelgrass meadows–coastal waters continuum in the protected and semi-enclosed coastal sea of Akkeshi-ko estuary (AKE) and Akkeshi Bay (AB), Japan from April 2014 to February 2015. The mixing dilution lines of the CDOM absorption coefficient at 355 nm [aCDOM(355)] relative to salinity predicted by two end-members between freshwater and coastal water showed conservative mixing in AB. Silicate concentrations were significantly correlated with salinity and aCDOM(355) in AB in each month except for December 2014. These results suggest that silicate and CDOM in AB primarily originates from wetland-influenced river discharge. However, samples collected from the eelgrass meadows of AKE, where mariculture is developed, showed non-conservative mixing of silicate concentrations and aCDOM(355) with salinity except for June 2014. Elevated phosphate concentrations, probably released from sediments, were also found in the eelgrass meadows of AKE, especially during summer. These results suggest that the metabolic activities of mariculture and seagrass ecosystem significantly contribute to the nutrient cycles and CDOM absorption in AKE and to the distinct water-mass systems inside and outside AKE. The relative absorption properties of NAP [aNAP(443)], phytoplankton [aph(443)], and aCDOM(443) showed that CDOM is the main factor affecting the light distribution in AKE. However, the relative absorption properties varied seasonally in AB because of spring and autumn phytoplankton blooms and ice cover during winter. Significant relationships were observed between the Secchi disk depth (ZSD), aNAP(443), and aCDOM(443). Chl a concentration and aph(443) were not good indicators for predicting ZSD in our study region. These results suggest that incorporating inherent optical properties and CDOM from mariculture and seagrass ecosystem into ecosystem models could improve predictions of light distribution along the freshwater–eelgrass–coastal waters continuum in optically complex coastal waters.

Correlation signal processing for determination of the spatial distributions of temperature and acoustic characteristics of the medium

It is required in some applications to determine spatial temperature distribution inside investigated object, when direct measurement is impossible, and IR and microwave methods do not provide acceptable spatial resolution. For example, such problems arise in diagnostics of soft biological tissues lying at a depth of about 10 cm or more, and in hyperthermia. To do this, thermal acoustic radiation of the object can be used, which is similar to thermal electromagnetic radiation. It is required to solve the complicated inverse radiation-scattering problem. The intensiometric approach allows determining temperature by signal power measuring at each receiver and by subsequent processing. The correlation processing approach involves calculating the cross correlation functions for each pair of receivers. This approach improves the resolution. The acoustic field focusing is used to further improve the sensitivity and resolution. Moreover, the receiver system can be supplemented with transmitters creating a controlled noise field that is similar to the thermal acoustic field of the object. In this case, the algorithm is proposed that uses three data sets obtained under different experimental conditions. This algorithm allows to separately reconstruct the spatial distributions of temperature, absorption coefficient, and sound speed. [This study was supported by RFBR under Grant No. 21-32-70003]

Simultaneous reconstruction of optical absorption property and speed of sound in intravascular photoacoustic tomography

Intravascular photoacoustic tomography (IVPAT) is a newly developed imaging modality for the diagnosis and intervention of coronary artery diseases. It is an ill-posed nonlinear least squares (NLS) problem to recover the absorbed optical energy density (AOED) and optical absorption coefficient (OAC) distribution in the vascular cross sections from pressure photoacoustically generated by tissues with variable speed of sound (SoS). The prior knowledge of the SoS is usually unavailable before IVPAT scanning. The ideal assumption of a constant SoS leads to degraded image quality. This paper focuses on improvement of image quality for IVPAT in tissues with variable SoS by simultaneously recovering the SoS, AOED and OAC from the measured time-dependent pressure series. The joint recovery is implemented by alternately minimizing the errors between the measured and theoretical pressure by forward simulation. The demonstration results indicate that the normalized mean square absolute distance (NMSAD) of the reconstructions produced by this method is decreased by about 15% in comparison to that of the reconstructions with a fixed SoS. Comparison results show that this method outperforms the delay compensation method in recovering the AOED and the two-step algorithm in estimating the OAC by about 20% and 25% in NMSAD respectively.

Спектральные биооптические показатели вод Атлантического сектора Антарктики

Исследования изменчивости спектральных биооптических показателей вод Атлантического сектора Антарктики проводили в 79-м рейсе НИС «Академик Мстислав Келдыш» в период с 11.01.2020 по 04.02.2020. Получено, что концентрация хлорофилла a в сумме с феопигментами изменялась в исследованном слое на большинстве станций от 0,1 до 1,8 мг·м−3, за исключением двух станций, где достигала 2,2 и 4,4 мг·м−3. Установлена связь показателей поглощения света пигментами фитопланктона с концентрацией хлорофилла a на длинах волн, соответствующих основным максимумам спектра: aph(438) = 0,044 × Ca1,2, r2 = 0,84 (n = 117); aph(678) = 0,021 × Ca1,1, r2 = 0,89 (n = 117). Спектры показателей поглощения света неживым взвешенным веществом и окрашенным растворённым органическим веществом описаны экспоненциальной зависимостью. Подобраны коэффициенты параметризации: (1) показатели поглощения света неживым взвешенным (0,001–0,027 м−1) и растворённым органическим веществом (0,016–0,19 м−1) на длине волны 438 нм; (2) коэффициенты наклона экспоненты спектров этих компонент (0,005–0,016 и 0,009–0,022 нм−1 соответственно).

In situ observation with x-ray for tentative exploration of laser beam welding processes for aluminum-based alloys

In recent years, laser processes have taken an ever-increasing market share in the manufacture of components. The development of new, improved beam sources with corresponding systems technology and the decreasing investment costs of the beam sources are important keys to this success. Particularly, high frequency beam oscillation has great potential in laser beam welding and cutting. The main obstacle for the widespread breakthrough of high frequency (HF) beam oscillation is the still insufficient understanding of the underlying physical mechanisms. Gaining a deeper insight is essential for process optimization. The in situ observation with x rays enables the visualization and analysis of these highly dynamic processes inside the workpiece. The goal of the performed experiment described in this paper was to in situ analyze the structural evolution of and defect generation in laser welding beads of different aluminum alloys. A fiber laser (max. 600 W, cw output power) including a beam scanner control system for rapid beam guidance was used. Of general interest was the comparison between static and oscillated beam guidance and the effects on the joining procedure. This paper shows the initial results of the analysis of the melt pool behavior and seam formation as well as the formation of seam irregularities during the laser process. In the simplest case, radiographs were taken, i.e., 2D projections of the x-ray absorption coefficient distribution within a material. Thereby, recordings from 10 000 up to 40 000 fps could be generated. Furthermore, tomoscopies—the continuous acquisition of tomographic (3D) images, up to 100 tomograms per second—could be generated with proven equipment, whose main components are a high-speed rotation stage and a camera system. The findings will help to get a better understanding of keyhole phenomena as well as effects of turbulent melt flow such as pore formation and guide to solutions for preventing them. Hence, initial results of high frequency beam oscillation processes including melt pool degassing and porosity reduction will be shown and discussed.

The Study on Structural and Photoelectric Properties of Zincblende InGaN via First Principles Calculation

In this paper, the structure and photoelectric characteristics of zincblende InxGa1−xN alloys are systematically calculated and analyzed based on the density functional theory, including the lattice constant, band structure, distribution of electronic states, dielectric function, and absorption coefficient. The calculation results show that with the increase in x, the lattice constants and the supercell volume increase, whereas the bandgap tends to decrease, and InxGa1−xN alloys are direct band gap semiconductor materials. In addition, the imaginary part of the dielectric function and the absorption coefficient are found to redshift with the increase in indium composition, expanding the absorption range of visible light. By analyzing the lattice constants, polarization characteristics, and photoelectric properties of the InxGa1−xN systems, it is observed that zincblende InxGa1−xN can be used as an alternative material to replace the channel layer of wurtzite InxGa1−xN heterojunction high electron mobility transistor (HEMT) devices to achieve the manufacture of HEMT devices with higher power and higher frequency. In addition, it also provides a theoretical reference for the practical application of InxGa1−xN systems in optoelectronic devices.

Dynamic pulse propagation modelling for predictive femtosecond-laser-microbonding of transparent materials.

A dynamic pulse propagation modeling for femtosecond laser bonding of Borofloat glass is presented. The temperature evolution and internal modifications are predicted by incorporating the nonlinear electron dynamics along with temperature dependent thermal properties. The modelling predicts the spatial and temporal distribution of absorption coefficient and plasma density that gives quantitative estimations of the heat affected zone and weld geometry. The impact of focusing condition on heat affected zone and weld geometry is investigated, which for the first time to our knowledge allows to numerically determine the desired relative position between the geometrical focus of a femtosecond-laser-pulse and the interface of the two substrates to be welded. The prediction of the modelling on the offset distance is applied to weld Borofloat glass plates having optical contact and can be applied to other dielectric solids.

Ultrasonic tomograph for reconstruction of spatial distributions of sound speed and absorption coefficient

Ultrasound tomograph designed to reconstruct spatial distributions of sound speed and absorption coefficient in soft biological tissues (primarily in mammary gland) is presented. Distinctive feature of the tomograph is sparse annular antenna array with irregular arrangement of receiving-transmitting transducers. When an object is tomographed by its layers, 26 transducers in combination with antenna rotation allow providing the same data set as in case of nonrotating array with 256 transducers. Two-step processing algorithm uses both ray methods to reconstruct large-scale details of the required spatial distributions and wave methods to reconstruct small details. High degree of algorithm parallelism allows to reduce the time of experimental data processing by CUDA GPUs to several minutes per an image layer. Results of processing both model data and experimental data obtained for phantom objects are presented. Disadvantages of reconstruction at the first step of the algorithm with low resolution (0.5–1 cm) are analyzed. The high resolution (not worse than 1 mm), achieved at the second step of reconstructing the small details is illustrated. It is shown that these small details, which are the most informative for medical diagnostics at early stage of neoplasm, cannot be reconstructed without preliminary reconstruction of large-scale details.