Experimental 3-D Ultrasound Imaging with 2-D Sparse Arrays using Focused and Diverging Waves

Abstract

Three dimensional ultrasound (3-D US) imaging methods based on 2-D array probes are increasingly investigated. However, the experimental test of new 3-D US approaches is contrasted by the need of controlling very large numbers of probe elements. Although this problem may be overcome by the use of 2-D sparse arrays, just a few experimental results have so far corroborated the validity of this approach. In this paper, we experimentally compare the performance of a fully wired 1024-element (32 × 32) array, assumed as reference, to that of a 256-element random and of an “optimized” 2-D sparse array, in both focused and compounded diverging wave (DW) transmission modes. The experimental results in 3-D focused mode show that the resolution and contrast produced by the optimized sparse array are close to those of the full array while using 25% of elements. Furthermore, the experimental results in 3-D DW mode and 3-D focused mode are also compared for the first time and they show that both the contrast and the resolution performance are higher when using the 3-D DW at volume rates up to 90/second which represent a 36x speed up factor compared to the focused mode.

3-D Super-Resolution Ultrasound Imaging Using a 2-D Sparse Array with High Volumetric Imaging Rate

“…In this study, a density-tapered sparse array method was chosen instead of a full 2-D array to reduce the number of channels and hence the amount of data while maintaining the frame rate. This approach is similar to previous studies on minimally redundant 2-D arrays [22] and sparse 2-D arrays [23]- [27], but uses more number of elements to improve transmit power and receive sensitivity. Our method significantly differs from row-column addressing and multiplexing approaches since it maintains simultaneous access to all probe elements through independent channels.…”

Sparse Rectangular and Spiral Array Designs for 3D Medical Ultrasound Imaging

“…Note that the angular positions {α n } in Equation 18can be illustrated with the active elements of the SLA shown in Figure 1 with d, P, L, and N P replaced by α 0 , P α , L α , and N Pα , respectively. Figure 4 shows some examples of the SSAs denoted by SSA(P α , L α ): (a) the sunflower array, (b) SSA(2,1), (c) SSA(4,1), (d) SSA (4,2), (e) SSA (3,1), and (f) SSA (3,2). Indeed, as shown in Figure 4, each of the SSAs defined by the polar coordinates 17is the spiral version of the corresponding SLA defined by Equation (18).…”

“…Ideally, if the element pitch was not greater than 0.5λ, then the grating lobes were not produced even when the focal point was steered. In this simulation, however, the element pitch (0.6λ) was chosen to be the same as that of a commercially available 2D array [4], which will be used in a future experimental study. Figure 5a shows the dense array pair on a 27 × 27 grid whose beam pattern will serve as the reference for the evaluation of beamforming performance of sparse arrays.…”

“…The sunflower array pair (Figure 11a) had the best performance with the highest MSR of 29.1 dB, lowest PGL of -47.2 dB, and the narrowest BW 50 of 20.22 • . All the SSA pairs that followed the design rule had PGL values below −40 dB, whereas TSA(2,1)/RSA(2,1) had a PGL of −37.3 dB even though it used the same number of elements as TSA(2,1)/RSA (4,2). Among the SSA pairs that follow the rule, the TSA(2,1)/RSA (3,2) pair, which used the largest number of active elements, had the best MSR (22.4 dB), PGL (−43.9 dB), and BW 50 (20.68 • ).…”

“…Placing elements irregularly is a reasonable approach to spread the concentrated grating lobe energy of a regular sparse array over the entire acoustic field [1]. This approach has been improved by using optimization theories [2][3][4]. In search of more reliable and computationally efficient sparse arrays, an analytical method utilizing the so-called almost difference sets (ADS) was also proposed [5].…”