The Effect of the transducer parameters on spatial resolution in Plane-Wave imaging

Alomari, Zainab; Harput, Sevan; Hyder, Safeer; Freear, Steven

doi:10.1109/ultsym.2015.0547

Cited by 12 publications

(5 citation statements)

References 13 publications

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“…Axial and lateral resolution results are both consistent with those reported in a previous study of plane-wave ultrasound imaging. 63 These results demonstrate the effect of ultrasound detector characteristics on system performance and show the potential of the proposed model for improving understanding of PAI device design consequences for particular imaging applications. Fig.…”

Section: Optical Beam Geometrymentioning

confidence: 66%

Multidomain computational modeling of photoacoustic imaging: verification, validation, and image quality prediction

et al. 2019

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As photoacoustic imaging (PAI) technology matures, computational modeling will increasingly represent a critical tool for facilitating clinical translation through predictive simulation of real-world performance under a wide range of device and biological conditions. While modeling currently offers a rapid, inexpensive tool for device development and prediction of fundamental image quality metrics (e.g., spatial resolution and contrast ratio), rigorous verification and validation will be required of models used to provide regulatory-grade data that effectively complements and/or replaces in vivo testing. To address methods for establishing model credibility, we developed an integrated computational model of PAI by coupling a previously developed three-dimensional Monte Carlo model of tissue light transport with a two-dimensional (2D) acoustic wave propagation model implemented in the well-known k-Wave toolbox. We then evaluated ability of the model to predict basic image quality metrics by applying standardized verification and validation principles for computational models. The model was verified against published simulation data and validated against phantom experiments using a custom PAI system. Furthermore, we used the model to conduct a parametric study of optical and acoustic design parameters. Results suggest that computationally economical 2D acoustic models can adequately predict spatial resolution, but metrics such as signal-to-noise ratio and penetration depth were difficult to replicate due to challenges in modeling strong clutter observed in experimental images. Parametric studies provided quantitative insight into complex relationships between transducer characteristics and image quality as well as optimal selection of optical beam geometry to ensure adequate image uniformity. Multidomain PAI simulation tools provide high-quality tools to aid device development and prediction of real-world performance, but further work is needed to improve model fidelity, especially in reproducing image noise and clutter.

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Section: Optical Beam Geometrymentioning

confidence: 66%

Multidomain computational modeling of photoacoustic imaging: verification, validation, and image quality prediction

et al. 2019

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“…The auto-correlation process produces maximum values when the same pattern signals detected and it reduces any unwanted side lobes or noises on the lateral direction. Meanwhile compounding process enhances the lateral resolution with FDMAS technique by averaging and cancelling the noises that present in lateral direction [8]- [10]. However, the same spatial improvement cant be seen on axial direction.…”

Section: Resultsmentioning

confidence: 97%

Enhancement of contrast and resolution of B-mode plane wave imaging (PWI) with non-linear filtered delay multiply and sum (FDMAS) beamforming

Moubark

Alomari

Harput

et al. 2016

2016 IEEE International Ultrasonics Symposium (IUS)

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“…Three different steering angles (−2 • , 0 • , +2 • ) were used, therefore reducing frame-rate from 10 kHz to 3.33 KHz [4]. Beamforming of RF data was performed using the traditional delay-andsum beamformer [15]. To increase the data sampling along the lateral dimension, RF data was beamformed with a lateral step size of 38.1 µm.…”

Section: A Data Acquisitionmentioning

confidence: 99%

A Novel Two-Dimensional Displacement Estimation for Angled Shear Wave Elastography

Hasnain

Hyder

Nie

et al. 2019

2019 IEEE International Ultrasonics Symposium (IUS)

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This study aimed to estimate angled tissue motion for shear wave compounding applications. Shear wave elastography produces the quantitative elasticity biomarker for assessing the health status of tissues. In sheer wave compounding, steered shear waves are generated with different angles, and individual angle elasticity maps are averaged to improve tissue stiffness reconstruction. When shear waves are steered and the tissue motion is generated in multiple directions, traditional one dimensional (1D) displacement estimation fails in capturing actual shear wave amplitude and direction. This study investigated the use of two dimensional (2D) kernel to track angular shear wave motion, which resulted in the underestimation of displacement values. Consequently, a new method named as 2D proposed (2D-P) was used to calculate both axial and lateral motion components separately using 1D axial and lateral kernels. Final results indicated that, the proposed scheme produced an average improvement of 2.01 µm and 4.4 µm compared with the 1D axial cross correlation and 2D cross correlation based methods, respectively.

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The Effect of the transducer parameters on spatial resolution in Plane-Wave imaging

Cited by 12 publications

References 13 publications

Multidomain computational modeling of photoacoustic imaging: verification, validation, and image quality prediction

Multidomain computational modeling of photoacoustic imaging: verification, validation, and image quality prediction

Enhancement of contrast and resolution of B-mode plane wave imaging (PWI) with non-linear filtered delay multiply and sum (FDMAS) beamforming

A Novel Two-Dimensional Displacement Estimation for Angled Shear Wave Elastography

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