Design, Implementation, and Medical Applications of 2-D Ultrasound Sparse Arrays

Abstract

An ultrasound sparse array consists of a 1 sparse distribution of elements over a 2-D aperture. Such 2 an array is typically characterized by a limited number 3 of elements, which in most cases is compatible with the 4 channel number of the available scanners. Sparse arrays 5 represent an attractive alternative to full 2-D arrays that 6 may require the control of thousands of elements through 7 expensive application-specific integrated circuits (ASICs). 8 However, their massive use is hindered by two main draw-9 backs: the possible beam profile deterioration, which may 10 worsen the image contrast, and the limited signal-to-noise 11 ratio (SNR), which may result too low for some applica-12 tions. This article reviews the work done for three decades 13 on 2-D ultrasound sparse arrays for medical applications. 14 First, random, optimized, and deterministic design meth-15 ods are reviewed together with their main influencing fac-16 tors. Then, experimental 2-D sparse array implementations 17 based on piezoelectric and capacitive micromachined ultra-18 sonic transducer (CMUT) technologies are presented. Sam-19 ple applications to 3-D (Doppler) imaging, super-resolution 20 imaging, photo-acoustic imaging, and therapy are reported. 21 The final sections discuss the main shortcomings associ-22 ated with the use of sparse arrays, the related countermea-23 sures, and the next steps envisaged in the development of 24 innovative arrays. 25 Index Terms-2-D arrays, 3-D ultrasound imaging, 26 capacitive micromachined ultrasonic transducer (CMUT), 27 genetic algorithm (GA), piezoelectric, simulated annealing 28 (SA), sparse arrays, spiral arrays, transducers. 29 I. INTRODUCTION 30 T HE introduction of 2-D arrays has greatly boosted the 31 development of novel ultrasound imaging methods aimed 32 Manuscript

Coherent Bistatic 3-D Ultrasound Imaging Using Two Sparse Matrix Arrays

“…Consequently, it did not increase between dual array monostatic imaging and bistatic imaging due to the added thermal noise, despite the additional high contrast wall regions between the transducers. Options to reduce the amount of thermal noise could be in hardware improvements such as more sensitive transducers and amplifiers [14]. As stated, the bistatic image formation improves image contrast and resolution, but also introduces some artefacts.…”

“…Bernal et al changed the transmit aperture between steering angles and found that the image quality can be improved with multiple complementary receiving sparse apertures, thereby decreasing 800 Hz volume rates with a factor 2-4 [13]. Sparse arrays with a higher center element density have also been increasingly used to optimize the homogeneity of the transmit field and non-periodic sampling of the elements to reduce the occurrence of grating lobes [14]. In terms of beam steering, comparisons in acquisition schemes suggest that a higher heterogeneity of compounded multi-angle transmits are favorable to improve both contrast and resolution [13,15].…”

Anatomic and Functional Imaging Using Row–Column Arrays

“…A straight forward translation to 3-D would give arrays with 192 × 192 = 36,864 elements or 256 × 256 = 65,536 elements yielding data rates of 2,560 GBytes/s, which is clearly not possible to process in real time. This has been solved by making sparse matrix probes, where only part of the elements are connected resulting in higher side lobe levels [1][2][3][4][5][6]. A second approach is to make micro-beamforming in the handle to reduce the amount of data.…”

Synthetic Aperture High Quality B-mode Imaging with a Row-Column Array Compared to Linear Array Imaging

“…Further, a doubling of resolution necessitates quadrupling the total number of elements. Many approaches for making sparse arrays have been suggested [3][4][5][6][7], but they suffer from reduced contrast and reduced penetration depth due to the reduction in active transducer surface area.…”