Abstract
Generally, ultrasound receive beamformers calculate the focusing time delays of fixed sound speeds in human tissue (e.g., 1540 m/s). However, phase distortions occur due to variations of sound speeds in soft tissues, resulting in degradation of image quality. Thus, an optimal estimation of sound speed is required in order to improve image quality. Implementation of real-time sound speed estimation is challenging due to high computational and hardware complexities. In this paper, an optimal sound speed estimation method with a low-cost hardware resource is presented. In the proposed method, the optimal mean sound speed is determined by measuring the amplitude variance of pre-beamformed radio-frequency (RF) data. The proposed method was evaluated with phantom and in vivo experiments, and implemented on Virtex-4 with Xilinx ISE 12.4 using VHDL. Experiment results indicate that the proposed method could estimate the mean optimal sound speed and enhance spatial resolution with a negligible increase in the hardware resource usage.
Highlights
Digital dynamic receive beamforming has been adopted for improving spatial resolution and contrast-to-noise ratios (CNRs) in medical ultrasound imaging [1,2,3]
We present a hardware-efficient optimal mean sound speed estimation method in which the focusing quality factor is measured by computing the minimum average sum of the absolute difference (MASAD) of pre-beamformed RF channel data, and enhance the spatial resolutions in medical ultrasound imaging
0.7% in slice LUTs and slice flip flops, respectively. These results indicate that the proposed method is capable of substantially improving the spatial resolution in medical ultrasound imaging and can be implemented with nearly a negligible increase in hardware complexity
Summary
Digital dynamic receive beamforming has been adopted for improving spatial resolution and contrast-to-noise ratios (CNRs) in medical ultrasound imaging [1,2,3]. A constant sound speed in human tissue (e.g., 1540 m/s) is typically assumed when generating dynamic receive focusing phase delays. Phase distortions are introduced due to the variations of sound speeds that occur in soft tissue, leading to defocusing and consequent degradations in image quality [4]. The degradation of image quality can significantly reduce diagnostic capability in breast or obese patient imaging, since the sound speed in fatty tissues (e.g., 1450 m/s) is lower than assumed value (e.g., 1540 m/s) [5]. Cross-correlation-based [6,7,8,9]
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