Efficient Sample Delay Calculation for 2-D and 3-D Ultrasound Imaging

Abstract

Abstract-Ultrasound imaging is a reference medical diagnostic technique thanks to its blend of versatility, effectiveness and moderate cost. The core computation of all ultrasound imaging methods is based on simple formulae, except for those required to calculate delays with high precision and throughput. Unfortunately, advanced 3D systems require the calculation or storage of billions of such delay values per frame, which is a challenge. In 2D systems, this requirement can be four orders of magnitude lower, but efficient computation is still crucial in view of low-power implementations that can be battery-operated, enabling usage in rescue scenarios.In this paper we explore two smart designs of the delay generation function. To quantify their hardware cost, we implement them on FPGA and study their footprint and performance. We evaluate how these architectures scale to different ultrasound applications, from a low-power 2D system to a next-generation 3D machine. When using numerical approximations, we demonstrate the ability to generate delay values with sufficient throughput to support 10000-channel 3D imaging at up to 30 fps while using 63% of a Virtex 7 FPGA, requiring 24 MB of external memory accessed at about 32 GB/s bandwidth. Alternatively, with similar FPGA occupation, we show an exact calculation method that reaches 24 fps on 1225-channel 3D imaging and does not require external memory at all. Both designs can be scaled to use a negligible amount of resources for 2D imaging in low-power applications, and for ultrafast 2D imaging at hundreds of frames per second.

Towards Ultrasound Everywhere: A Portable 3D Digital Back-End Capable of Zone and Compound Imaging

“…This work builds on top of previous publications by our group [10]- [12], [23]. The main contributions of this paper are: (i) a thorough discussion of the zone and compound imaging features, (ii) a detailed image quality assessment including contrast ratio and peak-signal-to-noise ratio, (iii) several platform optimizations to reduce resource utilization, and (iv) additional platform configurability, allowing e.g., runtime changes of image brightness, contrast, resolution, etc.…”

“…They are the main reason for the high power, cost, and area requirements of 3D US systems. As an example, in 3D imaging, a straightforward implementation of (1)-for a reasonable imager configuration and frame rate -leads to the need to calculate about 105 trillion delays/s [10]- [12]. Each delay value is calculated as the Euclidean distance from O to S then S to D, i.e., requiring two square roots.…”

“…In this work, we propose a novel, fullyscalable, complete, and single-FPGA US back-end system. We built our system around our previously proposed BF technique [10]- [12], [23]. In this design, an efficient and optimized method for each imaging step has been used to achieve overall platform efficiency, portability, and low power consumption.…”

“…The Tx delays are calculated using directly a Xilinx CORDIC core, as seen in Fig. 4(a) To solve the challenge of Rx delay calculation, we employ an efficient approximated algorithm [10]- [12]. It is based on the first order Taylor expansion of the square root.…”

“…In this paper, we assume the use of a phased array transducer, therefore the natural choice is a diverging beam. To achieve this, the emission origin O is virtually placed behind the transducer face [12]. SIRI offers the highest possible reconstruction rate-both in terms of echo acquisition and processing -and has very low memory requirements.…”