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High-Frequency Ultrasound Imaging With Sub-Nyquist Sampling

Jinbum Kang, Heechul Yoon, Changhan Yoon, Stanislav Emelianov

2022IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control13 citationsDOIOpen Access PDF

Abstract

Implementation of a high-frequency ultrasound (HFUS) beamformer is computationally challenging because of its high sampling rate. This article introduces an efficient beamformer with sub-Nyquist sampling (or bandpass sampling) that is suitable for HFUS imaging. Our approach used channel radio frequency data sampled at bandpass sampling rate (i.e., 4/ <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$3\textbf {f}_{\textbf {c}}$ </tex-math></inline-formula> ) and postfiltering-based interpolation to reduce the computational complexity. A polyphase structure for interpolation was used to further reduce the computational burden while maintaining an adequate delay resolution ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\boldsymbol {\delta }$ </tex-math></inline-formula> ). The performance of the proposed beamformer (i.e., 4/ <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$3\textbf {f}_{\textbf {c}}$ </tex-math></inline-formula> sampling with sixfold interpolation, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\boldsymbol {\delta } = 8\textbf {f}_{\textbf {c}}$ </tex-math></inline-formula> ) was compared with that of the conventional method (i.e., <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$4\textbf {f}_{\textbf {c}}$ </tex-math></inline-formula> sampling with fourfold interpolation, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\boldsymbol {\delta }= 16\textbf {f}_{\textbf {c}}$ </tex-math></inline-formula> ). Ultrafast coherent compounding imaging was used in simulation, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in vitro</i> and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in vivo</i> imaging experiments. Axial/lateral resolution and contrast-to-noise ratio (CNR) values were measured for quantitative evaluation. The number of transmit pulse cycles was varied from 1 to 3 using two transducers with different fractional bandwidths (67% and 98%). In the simulation, the proposed and conventional methods showed the similar −6-dB axial beam widths (63.5 and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$61.5~ \boldsymbol {\mu }\textbf {m}$ </tex-math></inline-formula> , respectively) from the two-cycle transmit pulse using the transducer with a bandwidth of 67%. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">In vitro</i> and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in vivo</i> imaging experiments were performed using a Verasonics ultrasound research platform equipped with a high-frequency array transducer (20–46 MHz). The <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in vitro</i> imaging results using a wire target showed consistent results with the simulation study (i.e., disparity <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$&lt; 5~ \boldsymbol {\mu }\textbf {m}$ </tex-math></inline-formula> at −6-dB axial resolution). The <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in vivo</i> feasibility study with a murine mouse model with breast cancer was also performed, and the proposed method yielded a similar image quality compared with the conventional method. From these studies, it was demonstrated that the proposed HFUS beamformer based on the bandpass sampling can substantially reduce the computational complexity while minimizing the loss of spatial resolution for HFUS imaging.

Topics & Concepts

UndersamplingSampling (signal processing)Interpolation (computer graphics)Bandwidth (computing)Nyquist–Shannon sampling theoremNyquist rateNyquist frequencyCenter frequencyTransducerAcousticsBeamformingComputer scienceImage resolutionBand-pass filterOpticsPhysicsFilter (signal processing)TelecommunicationsComputer visionFrame (networking)Ultrasound Imaging and ElastographyPhotoacoustic and Ultrasonic ImagingUltrasonics and Acoustic Wave Propagation