Modelling elastic wave propagation using the k-Wave MATLAB Toolbox

Treeby, Bradley E.; Jaroš, Jiří; Rohrbach, Daniel; Cox, Ben

doi:10.1109/ultsym.2014.0037

Cited by 95 publications

(75 citation statements)

References 12 publications

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“…The simulations were performed using both the fluid and elastic codes within the k-Wave toolbox [26,27]. The fluid code was used for most simulations, with the elastic code used to confirm that shear waves could be neglected.…”

Section: Simulation Setup Used For the Sensitivity Analysismentioning

confidence: 99%

“…Due to the increased computational burden of modelling elastic wave propagation, and the finer spatial discretisation required [30], the 3D simulation setup was translated into 2D. Simulations were carried out using the k-Wave 2D elastic PSTD code for 500 kHz, 750 kHz and 1 MHz ultrasound [27]. Two simulations were carried out at each frequency: a fluid simulation with shear speed set to zero throughout the domain, and an elastic simulation with appropriate shear speed and absorption values assigned to the bone layer.…”

Section: Effect Of Shear Waves In the Skullmentioning

confidence: 99%

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Sensitivity of simulated transcranial ultrasound fields to acoustic medium property maps

et al. 2017

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Abstract.High intensity transcranial focused ultrasound is an FDA approved treatment for essential tremor, while low-intensity applications such as neurostimulation and opening the blood brain barrier are under active research. Simulations of transcranial ultrasound propagation are used both for focusing through the skull, and predicting intracranial fields. Maps of the skull acoustic properties are necessary for accurate simulations, and can be derived from medical images using a variety of methods. The skull maps range from segmented, homogeneous models, to fully heterogeneous models derived from medical image intensity. In the present work, the impact of uncertainties in the skull properties is examined using a model of transcranial propagation from a single element focused transducer. The impact of changes in bone layer geometry and the sound speed, density, and acoustic absorption values is quantified through a numerical sensitivity analysis. Sound speed is shown to be the most influential acoustic property, and must be defined with less than 4% error to obtain acceptable accuracy in simulated focus pressure, position, and volume. Changes in the skull thickness of as little as 0.1 mm can cause an error in peak intracranial pressure of greater than 5%, while smoothing with a 1 mm 3 kernel to imitate the effect of obtaining skull maps from low resolution images causes an increase of over 50% in peak pressure. The numerical results are confirmed experimentally through comparison with sonications made through 3D printed and resin cast skull bone phantoms.

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Section: Simulation Setup Used For the Sensitivity Analysismentioning

confidence: 99%

Section: Effect Of Shear Waves In the Skullmentioning

confidence: 99%

Sensitivity of simulated transcranial ultrasound fields to acoustic medium property maps

et al. 2017

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“…We use here the elastic wave equation solver k-Wave [33], for the numerical solution using a given 3D heterogeneous model. The sensors and sources can be modelled with an arbitrary geometry and the simulations can be run faster on GPUs with single precision (32-bit representation) [34], [35].…”

Section: A Solving the Elastic Wave Equation On Gpus For Fast Synthementioning

confidence: 99%

“…In most of the geophysical simulation studies, the heterogeneous sound velocity and density model (together called the velocity model) are used for solving the forward problem of acoustic/elastic wave propagation through a viscoelastic medium [5], [3]. For the simulation of only the elastic case like in [6], [7], the viscous damping terms { } c c ρ as a 3D array (specified in each grid point) of the computational domain and uses a Fourier domain pseudo-spectral method for solving spatial derivatives in the coupled PDEs in (2) and a leapfrog finite-difference scheme for time marching (with a spatial and temporal staggered grid arrangement) as detailed in Treeby et al [33]- [35]. The pseudo-spectral method for computing spatial derivatives through fast Fourier transforms (FFTs) and its inverse (IFFT) makes the k-Wave solver computationally efficient and parallelizable over GPUs.…”

Section: A Solving the Elastic Wave Equation On Gpus For Fast Synthementioning

confidence: 99%

Fast GPU-Based Seismogram Simulation From Microseismic Events in Marine Environments Using Heterogeneous Velocity Models

Das

Chen

Hobson

2017

IEEE Trans. Comput. Imaging

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Abstract-A novel approach is presented for fast generation of synthetic seismograms due to microseismic events, using heterogeneous marine velocity models. The partial differential equations (PDEs) for the 3D elastic wave equation have been numerically solved using the Fourier domain pseudo-spectral method which is parallelizable on the graphics processing unit (GPU) cards, thus making it faster compared to traditional CPU based computing platforms. Due to computationally expensive forward simulation of large geological models, several combinations of individual synthetic seismic traces are used for specified microseismic event locations, in order to simulate the effect of realistic microseismic activity patterns in the subsurface. We here explore the patterns generated by few hundreds of microseismic events with different source mechanisms using various combinations, both in event amplitudes and origin times, using the simulated pressure and three component particle velocity fields via 1D, 2D and 3D seismic visualizations.

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“…The acoustic wave level simulations are based on a Matlab toolbox, i.e., k-Wave [11], which implements the pseudo-spectral and k-space method, discussed in Section 2, to solve acoustic wave propagation equations. The simulation consists of a 2-dimensional section of the human arm, including bones, muscles, fat and skin, as in [2].…”

Section: Multi-scale Simulatormentioning

confidence: 99%

A Comparison of MAC Protocols for Ultrasonic Intra-body Sensor Networks

Santagati

Gradillo

Cuomo

et al. 2014

Proceedings of the 9th International Conference on Body Area Networks

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Wireless intra-body networks of implantable biomedical devices have the potential to enable revolutionary healthcare and clinical applications. In our previous work we investigated the use of ultrasonic waves as an alternative to radio frequency (RF) waves as physical carrier of information, and proposed Ultrasonic WideBand (UsWB), the first ultrasonic integrated physical and medium access control (MAC) layer protocol.In this paper, we compare the performance of the UsWB MAC protocol with two existing MAC protocols originally designed for wireless RF-based networks, ALOHA and Carrier Sense Multiple Access (CSMA). In particular, we discuss the protocol performance in terms of (i) average network throughput and packet drop rate, (ii) average short-term fairness, (iii) average packet delay and packet delay variation, and (iv) energy consumption per bit. We show that UsWB outperforms ALOHA in terms of throughput, while CSMA can achieve comparable performance under specific setups. However, both ALOHA and CSMA have very high packet drop rates as compared to UsWB. The latter is capable of keeping the packet drop rate under a pre-defined threshold. Moreover, UsWB significantly outperforms both ALOHA and CSMA in terms of short-term fairness, average packet delays and delay variation. Finally, CSMA has the highest energy consumption per bit, because of long idle sensing times, whereas UsWB has the lowest, and it can be further reduced by trading throughput for energy consumption through energy-minimizing rate adaptation.

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Modelling elastic wave propagation using the k-Wave MATLAB Toolbox

Cited by 95 publications

References 12 publications

Sensitivity of simulated transcranial ultrasound fields to acoustic medium property maps

Sensitivity of simulated transcranial ultrasound fields to acoustic medium property maps

Fast GPU-Based Seismogram Simulation From Microseismic Events in Marine Environments Using Heterogeneous Velocity Models

A Comparison of MAC Protocols for Ultrasonic Intra-body Sensor Networks

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