Fourier-based Synthetic-aperture Imaging for Arbitrary Transmissions by Cross-correlation of Transmitted and Received Wave-fields

2021 ◽  
pp. 016173462110263
Author(s):  
Rehman Ali

Investigations into Fourier beamforming for medical ultrasound imaging have largely been limited to plane-wave and single-element transmissions. The main aim of this work is to generalize Fourier beamforming to enable synthetic aperture imaging with arbitrary transmit sequences. When applied to focused transmit beams, the proposed approach yields a full-waveform-based alternative to virtual-source synthetic aperture, which has implications for both coherence imaging and sound speed estimation. When compared to virtual-source synthetic aperture and retrospective encoding for conventional ultrasound sequences (REFoCUS), the proposed imaging technique shows an 8.6 and 3.8 dB improvement in contrast over virtual source synthetic aperture and REFoCUS, respectively, and a 55% improvement in point target resolution over virtual source synthetic aperture. The proposed image reconstruction technique also demonstrates general imaging improvements in vivo, while avoiding limitations seen in prior techniques.

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2275
Author(s):  
Hae Gyun Lim ◽  
Hyung Ham Kim ◽  
Changhan Yoon

High-frequency ultrasound (HFUS) imaging has emerged as an essential tool for pre-clinical studies and clinical applications such as ophthalmic and dermatologic imaging. HFUS imaging systems based on array transducers capable of dynamic receive focusing have considerably improved the image quality in terms of spatial resolution and signal-to-noise ratio (SNR) compared to those by the single-element transducer-based one. However, the array system still suffers from low spatial resolution and SNR in out-of-focus regions, resulting in a blurred image and a limited penetration depth. In this paper, we present synthetic aperture imaging with a virtual source (SA-VS) for an ophthalmic application using a high-frequency convex array transducer. The performances of the SA-VS were evaluated with phantom and ex vivo experiments in comparison with the conventional dynamic receive focusing method. Pre-beamformed radio-frequency (RF) data from phantoms and excised bovine eye were acquired using a custom-built 64-channel imaging system. In the phantom experiments, the SA-VS method showed improved lateral resolution (>10%) and sidelobe level (>4.4 dB) compared to those by the conventional method. The SNR was also improved, resulting in an increased penetration depth: 16 mm and 23 mm for the conventional and SA-VS methods, respectively. Ex vivo images with the SA-VS showed improved image quality at the entire depth and visualized structures that were obscured by noise in conventional imaging.


2013 ◽  
Vol 60 (10) ◽  
pp. 2716-2724 ◽  
Author(s):  
Choye Kim ◽  
Changhan Yoon ◽  
Jong-Ho Park ◽  
Yuhwa Lee ◽  
Won Hwa Kim ◽  
...  

2002 ◽  
Vol 24 (2) ◽  
pp. 81-99 ◽  
Author(s):  
K.S. Kim ◽  
J.S. Hwang ◽  
J.S. Jeong ◽  
T.K. Song

This paper describes a method for overcoming motion artifacts in synthetic aperture imaging. The method is based on a computer simulation study on the influence of target motion on synthetic aperture techniques. A region-based motion compensation approach is used in which only the axial motion is estimated and compensated for a given region of interest under the assumption that the whole ROI moves uniformly. The estimated axial motion is calculated with a crosscorrelation method at the point where the focused signal has the maximum energy within the ROI. We also present a method for estimating axial motion using the autocorrelation method that is widely used to estimate average Doppler frequency. Both computer simulations and in vivo experiments show that the proposed crosscorrelation-based method can greatly improve the spatial resolution and SNR of ultrasound imaging by implementing SA techniques for two-way dynamic focusing without motion artifacts. In addition, the autocorrelation-based motion compensation method provides almost the same results as the crosscorrelation-based method, but with a dramatically reduced computational complexity.


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