Fourier f-k migration for plane wave ultrasound imaging: Theoretical framework

Tarnec, Louis Le; Muth, Stéphan; Montagnon, Emmanuel; Porée, Jonathan; Cloutier, Guy; Garcia, Damien

doi:10.1109/ultsym.2012.0534

Cited by 3 publications

(9 citation statements)

References 4 publications

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“…The migration is an inverse problem because the recorded waves are those transmitted and returned and they correspond to the localization of a certain reflector [ 20 ]. Based on Stolt’s proposal where a Fast Fourier Transform (FFT) is introduced, this method has been adapted for use in the plane wave mode [ 21 , 22 ]. The FFT used for US beamforming has been studied since the beginning of the 1980s [ 23 ].…”

Section: Methodsmentioning

confidence: 99%

“…The method used in the work of Tarnec et al and Garcia et al was based on the Exploding Reflector Model (ERM), which assumes that all reflectors on the medium simultaneously explodes [ 21 , 22 ]. In this process, the wavefield considers that the explosion time is t = 0, becoming an acoustic issuing source.…”

Section: Methodsmentioning

confidence: 99%

“…Traditionally, each transducer element transmits the pulse signal and receives the echo in a pulse-echo operation mode. In this configuration, the traveling time (τ s ) from the target at ( x s , z s ) to the transducer, depending on the position of each transducer element, can be calculated as in Equation (4) [ 21 , 22 ], where c is the speed of sound in the medium:

…”

Section: Methodsmentioning

confidence: 99%

“…The Stolt migration is focused on the reverse wave propagation time, that is, the return time of the signal after the ERM explosion. Thus, it is enough to determine the signal’s return time to the sensor and not its total time (Equation (5)), where the e index means that the echo signal comes from the ERM position [ 21 , 22 ]:

…”

Section: Methodsmentioning

confidence: 99%

“…The whole method described above and the sample routines are presented in [ 21 , 22 ]. So, the steps for image reconstruction using the Stolt migration technique are: Filtering of the raw signal Applying the FFT to the data Correction for the excitation angles Interpolation for a new scale Apply the inverse FFT to the data Additional filtering (optional) …”

Section: Methodsmentioning

confidence: 99%

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Generation and Analysis of Ultrasound Images Using Plane Wave and Sparse Arrays Techniques

Schiefler

Maia

Schneider

et al. 2018

Sensors

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Ultrasonic imaging is one of the most important techniques to help medical diagnosis. However, obtaining high quality images requires the acquisition, processing, and storage of a large amount of data. In this work, we evaluated a new ultrasound imaging technique based on plane wave and sparse arrays to increase the scan rate and reduce the amount of data amount to be stored. The performance of the proposed method was tested using simulated echo data (from Field II) and phantom data acquired using a Verasonics system equipped with a L11-4v linear array transducer. The tests were done using 128 elements for transmission and 128, 65, 44, and 23 elements sparsely distributed for reception. The simulated data were compared with images obtained with the Delay and Sum (DAS) method and the experimental data were compared with those acquired from Verasonics. The obtained results using the Full Width at Half Maximum (FWHM) criteria at −6 dB showed that the images generated by the proposed method were similar in terms of resolutions (axial and lateral) and contrast to the simulated and the Verasonics commercial ones, indicating that the sparse reception proposed method is suitable for ultrasound imaging.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

…”

Section: Methodsmentioning

confidence: 99%

…”

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Generation and Analysis of Ultrasound Images Using Plane Wave and Sparse Arrays Techniques

Schiefler

Maia

Schneider

et al. 2018

Sensors

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Stratified-Medium Sound Speed Profiling for CPWC Ultrasound Imaging

D'Souza

Rakhmatov

2020

2020 IEEE International Ultrasonics Symposium (IUS)

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Coherent plane-wave compounding (CPWC) ultrasound is an important modality enabling ultrafast biomedical imaging. To perform CWPC image reconstruction for a stratified (horizontally layered) medium, one needs to know how the speed of sound (SOS) varies with the propagation depth. Incorrect sound speed and layer thickness assumptions can cause focusing errors, degraded spatial resolution and significant geometrical distortions resulting in poor image reconstruction. We aim to determine the speed of sound and thickness values for each horizontal layer to accurately locate the recorded reflection events to their true locations within the medium. Our CPWC image reconstruction process is based on phase-shift migration (PSM) that requires the user to specify the speed of sound and thickness of each layer in advance. Prior to performing phase-shift migration (one layer at a time, starting from the surface), we first estimate the speed of sound values of a given layer using a cosine similarity metric, based on the data obtained by a multi-element transducer array for two different plane-wave emission angles. Then, we use our speed estimate to identify the layer thickness via end-of-layer boundary detection. A low-cost alternative that obtains reconstructed images with fewer phase shifts (i.e., fewer complex multiplications) using a spectral energy threshold is also proposed in this thesis. Our evaluation results, based on the CPWC imaging simulation of a three-layer medium, show that our sound speed and layer thickness estimates are within 4% of their true values (i.e., those used to generate simulated data). We have also confirmed the accuracy of our speed and layer thickness estimation separately, using two experimental datasets representing two special cases. For speed estimation, we used iv a CPWC imaging dataset for a constant-speed (i.e., single-layer) medium, yielding estimates within 1% of their true values. For layer thickness estimation, we used a monostatic (i.e., single-element) synthetic-aperture (SA) imaging dataset of the threelayer medium, also yielding estimates within 1% of their true values. Our evaluation results for the low-cost alternative showed a 93% reduction in complex multiplications for the three-layer CPWC imaging dataset and 76% for the three-layer monostatic SA imaging dataset, producing images nearly similar to those obtained using the original PSM methods.

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What Indicative Information of a Subsurface Wetted Body Can Be Detected by a Ground-Penetrating Radar (GPR)? A Laboratory Study and Numerical Simulation

et al. 2022

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Nondestructive and noninvasive visualization and quantification of soil wetted bodies (SWBs) is of great significance to the development of water-saving agriculture. Unfortunately, measuring the parameters of SWBs is difficult due to the invisibility of SWBs buried underneath the ground and the non-variability of the soil moisture under partial irrigation conditions. Therefore, we performed a laboratory experiment to investigate what SWB attributes can be detected by a GPR. In the laboratory, three typical partial irrigation experiments were conducted to collect the GPR data of SWBs of different sizes, shapes, and burial depths. Additionally, numerical simulation scenarios were designed according to the laboratory experiment. Then, the simulated and measured GPR data were processed by the FK migration method. Based on the simulation, a calibration model for the width of SWBs was constructed. We found that SWB attributes, such as type and location can be obtained from raw radargrams owing to the obvious reflection of the top and bottom interfaces. The results showed that estimating the depth and thickness of SWBs from FK migration radargrams is more reliable than from raw radargrams. Moreover, estimation of the width of SWBs relies on the FK migration radargrams. Our findings indicate that the size and depth of SWBs dominate the width detection accuracy, and the estimated width gained via the width calibration model is improved. Our results highlight the potential for using GPR data to detect SWBs, as well as the potential of using numerical simulation, FK migration, and calibration modeling in combination to extract the size information of SWBs from GPR radargrams.

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Fourier f-k migration for plane wave ultrasound imaging: Theoretical framework

Cited by 3 publications

References 4 publications

Generation and Analysis of Ultrasound Images Using Plane Wave and Sparse Arrays Techniques

Generation and Analysis of Ultrasound Images Using Plane Wave and Sparse Arrays Techniques

Stratified-Medium Sound Speed Profiling for CPWC Ultrasound Imaging

What Indicative Information of a Subsurface Wetted Body Can Be Detected by a Ground-Penetrating Radar (GPR)? A Laboratory Study and Numerical Simulation

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