Persistence of Structural Distortion and Bulk Band Rashba Splitting in SnTe above Its Ferroelectric Critical Temperature.

The ferroelectric semiconductor α-SnTe has been regarded as a topological crystalline insulator, and the dispersion of its surface states has been intensively measured with angle-resolved photoemission spectroscopy (ARPES) over the past decade. However, much less attention has been given to the impact of the ferroelectric transition on its electronic structure, and in particular on its bulk states. Here, we investigate the low-energy electronic structure of α-SnTe with ARPES and follow the evolution of the bulk-state Rashba splitting as a function of temperature, across its ferroelectric critical temperature of about Tc ≈ 110 K. Unexpectedly, we observe a persistent band splitting up to room temperature, which is consistent with an order-disorder contribution of local dipoles to the phase transition that requires the presence of fluctuating dipoles above Tc. We conclude that no topological surface state can occur under these conditions at the (111) surface of SnTe, at odds with recent literature.

Single-stage approach for estimating optical parameters in spectral quantitative photoacoustic tomography.

In quantitative photoacoustic tomography, the optical parameters of a target, most importantly the concentrations of chromophores such as deoxygenated and oxygenated hemoglobin, are estimated from photoacoustic data measured on the boundary of the target. In this work, a numerical approximation of a forward model for spectral quantitative photoacoustic tomography is constructed by utilizing the diffusion approximation for light propagation, the acoustic wave equation for ultrasound propagation, and spectral models of optical absorption and scattering to describe the wavelength dependence of the optical parameters. The related inverse problem is approached in the framework of Bayesian inverse problems. Concentrations of four chromophores (deoxygenated and oxygenated hemoglobin, water, and lipid), two scattering parameters (reference scattering and scattering power), and the Grüneisen parameter are estimated in a single-stage from photoacoustic data. The methodology is evaluated using numerical simulations in different full-view and limited-view imaging settings. The results show that, utilizing spectral data and models, the spectral optical parameters and the Grüneisen parameter can be simultaneously estimated. Furthermore, the approach can also be utilized in limited-view imaging situations.

Background-oriented schlieren sensitivity in terms of geometrical parameters of measurement setup.

Background-oriented schlieren imaging is a recently proposed noninvasive optical method for imaging of full ultrasound fields. In this work, the impact of uncertainty in geometrical parameters of a background-oriented schlieren measurement setup for imaging of full ultrasound fields is studied using numerical simulations. The studied parameters are focal length of the camera and positions and orientations of the camera, water tank, and ultrasound field. The results demonstrate that the most sensitive parameters affecting the accuracy of the reconstructed ultrasound fields are the orientations of the camera that change the direction of an effective optical axis. Other sensitive parameters are the focal length of the camera and the position of the ultrasound field in perpendicular directions of an optical axis. This synthetic study demonstrates the accuracy requirements for calibrating the geometrical parameters of a measurement setup that would be required to achieve accuracy comparable to that of hydrophone measurements using the background-oriented schlieren imaging. Explicitly, limits of the variation ranges of the geometrical parameters resulting in relative error ranges of 5% and 10% are given. The results of this study may contribute to help design future background-oriented schlieren measurement setups intended for measurement of full ultrasound fields.

Nonlinear estimation of pressure projection of ultrasound fields in background-oriented schlieren imaging.

Background-oriented schlieren imaging is a recently proposed method for measuring projections of ultrasound fields. The method is based on observing deflection of light in a heterogeneous refractive index field that is induced by ultrasound via an acousto-optic effect. The deflection of light manifests as apparent perturbations in an imaged target, forming a potential flow estimation problem. In this work, the potential flow approach is formulated as a nonlinear regularized least-squares approach to alleviate limitations of approaches that linearize the problem. The nonlinear approach is shown to outperform the linear one when estimating projections of medically relevant ultrasound fields.

Benchmark problems for transcranial ultrasound simulation: Intercomparison of compressional wave models.

Computational models of acoustic wave propagation are frequently used in transcranial ultrasound therapy, for example, to calculate the intracranial pressure field or to calculate phase delays to correct for skull distortions. To allow intercomparison between the different modeling tools and techniques used by the community, an international working group was convened to formulate a set of numerical benchmarks. Here, these benchmarks are presented, along with intercomparison results. Nine different benchmarks of increasing geometric complexity are defined. These include a single-layer planar bone immersed in water, a multi-layer bone, and a whole skull. Two transducer configurations are considered (a focused bowl and a plane piston operating at 500 kHz), giving a total of 18 permutations of the benchmarks. Eleven different modeling tools are used to compute the benchmark results. The models span a wide range of numerical techniques, including the finite-difference time-domain method, angular spectrum method, pseudospectral method, boundary-element method, and spectral-element method. Good agreement is found between the models, particularly for the position, size, and magnitude of the acoustic focus within the skull. When comparing results for each model with every other model in a cross-comparison, the median values for each benchmark for the difference in focal pressure and position are less than 10% and 1 mm, respectively. The benchmark definitions, model results, and intercomparison codes are freely available to facilitate further comparisons.

Acoustic pressure field estimation methods for synthetic schlieren tomography.

Synthetic schlieren tomography is a recently proposed three-dimensional (3D) optical imaging technique for studying ultrasound fields. The imaging setup is composed of an imaged target, a water tank, a camera, and a pulsed light source, which is stroboscopically synchronized with an ultrasound transducer to achieve tomographically stationary imaging of an ultrasound field. In this technique, ultrasound waves change the propagation of light rays by inducing a change in refractive index via the acousto-optic effect. The change manifests as optical flow in the imaged target. By performing the imaging in a tomographic fashion, the two-dimensional tomographic dataset of the optical flow can be transformed into a 3D ultrasound field. In this work, two approaches for acoustic pressure field estimation are introduced. The approaches are based on optical and potential flow regularized least square optimizations where regularization based on the Helmholtz equation is introduced. The methods are validated via simulations in a telecentric setup and are compared quantitatively and qualitatively to a previously introduced method. Cases of a focused, an obliquely propagating, and a standing wave ultrasound field are considered. The simulations demonstrate the efficiency of the introduced methods also in situations in which the previously applied method has weaknesses.

Three dimensional photoacoustic tomography in Bayesian framework.

The image reconstruction problem (or inverse problem) in photoacoustic tomography is to resolve the initial pressure distribution from detected ultrasound waves generated within an object due to an illumination by a short light pulse. Recently, a Bayesian approach to photoacoustic image reconstruction with uncertainty quantification was proposed and studied with two dimensional numerical simulations. In this paper, the approach is extended to three spatial dimensions and, in addition to numerical simulations, experimental data are considered. The solution of the inverse problem is obtained by computing point estimates, i.e., maximum a posteriori estimate and posterior covariance. These are computed iteratively in a matrix-free form using a biconjugate gradient stabilized method utilizing the adjoint of the acoustic forward operator. The results show that the Bayesian approach can produce accurate estimates of the initial pressure distribution in realistic measurement geometries and that the reliability of these estimates can be assessed.

Ultrasound field characterization using synthetic schlieren tomography.

Synthetic schlieren imaging, also known as background oriented schlieren imaging, is used to determine the acoustical field of a focused ultrasound transducer operating at 1.01 MHz frequency with peak pressure amplitude of 0.97 MPa. The measurement setup is composed of a commercial off-the-shelf digital single-lens reflex (DSLR) camera with an ordinary objective, a high power light-emitting diode driven in pulsating mode, water tank, ultrasound transducer, rotation stage, and driving electronics. Measurements are performed in tomographic fashion by rotating the ultrasound transducer within the water tank and photographing an imaged target behind the ultrasound field. The photographs are processed with a Horn-Schunck-type algorithm, commonly used in optical flow analysis, in order to determine the deflection of light rays as caused by ultrasound field induced acousto-optic effect. Inverse Radon transform is then used, with the deflection data, to obtain three-dimensional spatial distribution of the pressure field gradient, from which an approximation of the ultrasonic pressure field is computed. The pressure field obtained with synthetic schlieren tomography is then compared to hydrophone measurements mainly qualitatively.

Image reconstruction with uncertainty quantification in photoacoustic tomography.

Photoacoustic tomography is a hybrid imaging method that combines optical contrast and ultrasound resolution. The goal of photoacoustic tomography is to resolve an initial pressure distribution from detected ultrasound waves generated within an object due to an illumination of a short light pulse. In this work, a Bayesian approach to photoacoustic tomography is described. The solution of the inverse problem is derived and computation of the point estimates for image reconstruction and uncertainty quantification is described. The approach is investigated with simulations in different detector geometries, including limited view setup, and with different detector properties such as ideal point-like detectors, finite size detectors, and detectors with a finite bandwidth. The results show that the Bayesian approach can be used to provide accurate estimates of the initial pressure distribution, as well as information about the uncertainty of the estimates.

Truncated Fourier-series approximation of the time-domain radiative transfer equation using finite elements.

The radiative transfer equation (RTE) is widely accepted to accurately describe light transport in a medium with scattering particles, and it has been successfully applied as a light-transport model, for example, in diffuse optical tomography. Due to the computationally expensive nature of the RTE, most of these applications have been in the frequency domain. In this paper, an efficient solution method for the time-domain RTE is proposed. The method is based on solving the frequency-domain RTE at multiple modulation frequencies and using the Fourier-series representation of the radiance to obtain approximation of the time-domain solution. The approach is tested with simulations. The results show that the method can be used to obtain the solution of the time-domain RTE with good accuracy and with significantly fewer computational resources than are needed in the direct time-domain solution.

Adaptive stochastic Gauss-Newton method with optical Monte Carlo for quantitative photoacoustic tomography.

SIGNIFICANCE: The image reconstruction problem in quantitative photoacoustic tomography (QPAT) is an ill-posed inverse problem. Monte Carlo method for light transport can be utilized in solving this image reconstruction problem. AIM: The aim was to develop an adaptive image reconstruction method where the number of photon packets in Monte Carlo simulation is varied to achieve a sufficient accuracy with reduced computational burden. APPROACH: The image reconstruction problem was formulated as a minimization problem. An adaptive stochastic Gauss-Newton (A-SGN) method combined with Monte Carlo method for light transport was developed. In the algorithm, the number of photon packets used on Gauss-Newton (GN) iteration was varied utilizing a so-called norm test. RESULTS: The approach was evaluated with numerical simulations. With the proposed approach, the number of photon packets needed for solving the inverse problem was significantly smaller than in a conventional approach where the number of photon packets was fixed for each GN iteration. CONCLUSIONS: The A-SGN method with a norm test can be utilized in QPAT to provide accurate and computationally efficient solutions.

Computationally Efficient Forward Operator for Photoacoustic Tomography Based on Coordinate Transformations.

Photoacoustic tomography (PAT) is an imaging modality that utilizes the photoacoustic effect. In PAT, a photoacoustic image is computed from measured data by modeling ultrasound propagation in the imaged domain and solving an inverse problem utilizing a discrete forward operator. However, in realistic measurement geometries with several ultrasound transducers and relatively large imaging volume, an explicit formation and use of the forward operator can be computationally prohibitively expensive. In this work, we propose a transformation-based approach for efficient modeling of photoacoustic signals and reconstruction of photoacoustic images. In the approach, the forward operator is constructed for a reference ultrasound transducer and expanded into a general measurement geometry using transformations that map the formulated forward operator in local coordinates to the global coordinates of the measurement geometry. The inverse problem is solved using a Bayesian framework. The approach is evaluated with numerical simulations and experimental data. The results show that the proposed approach produces accurate 3-D photoacoustic images with a significantly reduced computational cost both in memory requirements and time. In the studied cases, depending on the computational factors, such as discretization, over the 30-fold reduction in memory consumption was achieved without a reduction in image quality compared to a conventional approach.

Break of symmetry at the surface of IrTe2upon phase transition measured by x-ray photoelectron diffraction.

IrTe2undergoes a series of charge-ordered phase transitions below room temperature that are characterized by the formation of stripes of Ir dimers of different periodicities. Full hemispherical x-ray photoelectron diffraction (XPD) experiments have been performed to investigate the atomic position changes undergone near the surface of 1T-IrTe2in the first-order phase transition, from the (1 × 1) phase to the (5 × 1) phase. Comparison between experiment and simulation allows us to identify the consequence of the dimerization on the Ir atoms local environment. We report that XPD permits to unveil the break of symmetry of IrTe2trigonal to a monoclinic unit cell and confirm the occurrence of the (5 × 1) reconstruction within the first few layers below the surface with a staircase-like stacking of dimers.

Modeling of Errors Due to Uncertainties in Ultrasound Sensor Locations in Photoacoustic Tomography.

Photoacoustic tomography is an imaging modality based on the photoacoustic effect caused by the absorption of an externally introduced light pulse. In the inverse problem of photoacoustic tomography, the initial pressure generated through the photoacoustic effect is estimated from a measured photoacoustic time-series utilizing a forward model for ultrasound propagation. Due to the ill-posedness of the inverse problem, errors in the forward model or measurements can result in significant errors in the solution of the inverse problem. In this work, we study modeling of errors caused by uncertainties in ultrasound sensor locations in photoacoustic tomography using a Bayesian framework. The approach is evaluated with simulated and experimental data. The results indicate that the inverse problem of photoacoustic tomography is sensitive even to small uncertainties in sensor locations. Furthermore, these uncertainties can lead to significant errors in the estimates and reduction of the quality of the photoacoustic images. In this work, we show that the errors due to uncertainties in ultrasound sensor locations can be modeled and compensated using Bayesian approximation error modeling.

Perturbation Monte Carlo Method for Quantitative Photoacoustic Tomography.

Quantitative photoacoustic tomography aims at estimating optical parameters from photoacoustic images that are formed utilizing the photoacoustic effect caused by the absorption of an externally introduced light pulse. This optical parameter estimation is an ill-posed inverse problem, and thus it is sensitive to measurement and modeling errors. In this work, we propose a novel way to solve the inverse problem of quantitative photoacoustic tomography based on the perturbation Monte Carlo method. Monte Carlo method for light propagation is a stochastic approach for simulating photon trajectories in a medium with scattering particles. It is widely accepted as an accurate method to simulate light propagation in tissues. Furthermore, it is numerically robust and easy to implement. Perturbation Monte Carlo maintains this robustness and enables forming gradients for the solution of the inverse problem. We validate the method and apply it in the framework of Bayesian inverse problems. The simulations show that the perturbation Monte Carlo method can be used to estimate spatial distributions of both absorption and scattering parameters simultaneously. These estimates are qualitatively good and quantitatively accurate also in parameter scales that are realistic for biological tissues.

Modelling of errors due to speed of sound variations in photoacoustic tomography using a Bayesian framework.

Inverse problem of estimating initial pressure in photoacoustic tomography is ill-posed and thus sensitive to errors in modelling and measurements. In practical experiments, accurate knowledge of the speed of sound of the imaged target is commonly not available, and therefore an approximate speed of sound is used in the computational model. This can result in errors in the solution of the inverse problem that can appear as artefacts in the reconstructed images. In this paper, the inverse problem of photoacoustic tomography is approached in a Bayesian framework. Errors due to uncertainties in the speed of sound are modelled using Bayesian approximation error modelling. Estimation of the initial pressure distribution together with information on the reliability of these estimates are considered. The approach was studied using numerical simulations. The results show that uncertainties in the speed of sound can cause significant errors in the solution of the inverse problem. However, modelling of these uncertainties improves the accuracy of the solution.

Quantitative photoacoustic tomography augmented with surface light measurements.

Quantitative photoacoustic tomography is an imaging modality in which distributions of optical parameters inside tissue are estimated from photoacoustic images. This optical parameter estimation is an ill-posed problem and it needs to be approached in the framework of inverse problems. In this work, utilising surface light measurements in quantitative photoacoustic tomography is studied. Estimation of absorption and scattering is formulated as a minimisation problem utilising both internal quantitative photoacoustic data and surface light data. The image reconstruction problem is studied with two-dimensional numerical simulations in various imaging situations using the diffusion approximation as the model for light propagation. The results show that quantitative photoacoustic tomography augmented with surface light data can improve both absorption and scattering estimates when compared to the conventional quantitative photoacoustic tomography.

Direct Estimation of Optical Parameters From Photoacoustic Time Series in Quantitative Photoacoustic Tomography.

Estimation of optical absorption and scattering of a target is an inverse problem associated with quantitative photoacoustic tomography. Conventionally, the problem is expressed as two folded. First, images of initial pressure distribution created by absorption of a light pulse are formed based on acoustic boundary measurements. Then, the optical properties are determined based on these photoacoustic images. The optical stage of the inverse problem can thus suffer from, for example, artefacts caused by the acoustic stage. These could be caused by imperfections in the acoustic measurement setting, of which an example is a limited view acoustic measurement geometry. In this work, the forward model of quantitative photoacoustic tomography is treated as a coupled acoustic and optical model and the inverse problem is solved by using a Bayesian approach. Spatial distribution of the optical properties of the imaged target are estimated directly from the photoacoustic time series in varying acoustic detection and optical illumination configurations. It is numerically demonstrated, that estimation of optical properties of the imaged target is feasible in limited view acoustic detection setting.

A numerical study on the oblique focus in MR-guided transcranial focused ultrasound.

Recent clinical data showing thermal lesions from treatments of essential tremor using MR-guided transcranial focused ultrasound shows that in many cases the focus is oblique to the main axis of the phased array. The potential for this obliquity to extend the focus into lateral regions of the brain has led to speculation as to the cause of the oblique focus, and whether it is possible to realign the focus. Numerical simulations were performed on clinical export data to analyze the causes of the oblique focus and determine methods for its correction. It was found that the focal obliquity could be replicated with the numerical simulations to within [Formula: see text] of the clinical cases. It was then found that a major cause of the focal obliquity was the presence of sidelobes, caused by an unequal deposition of power from the different transducer elements in the array at the focus. In addition, it was found that a 65% reduction in focal obliquity was possible using phase and amplitude corrections. Potential drawbacks include the higher levels of skull heating required when modifying the distribution of power among the transducer elements, and the difficulty at present in obtaining ideal phase corrections from CT information alone. These techniques for the reduction of focal obliquity can be applied to other applications of transcranial focused ultrasound involving lower total energy deposition, such as blood-brain barrier opening, where the issue of skull heating is minimal.