Rhombic Grids Reduce the Number of Voxels in Fast Pulse-Echo Ultrasound Imaging

TL;DR

This paper introduces rhombic grids for ultrasound imaging that significantly reduce voxel count, lowering computational costs while maintaining image quality, based on spectral properties and validated through phantom experiments.

Contribution

The paper proposes a novel rhombic grid design for ultrasound imaging that reduces voxel numbers by over 80%, improving efficiency without compromising image quality.

Findings

Voxel reduction of 81.4% compared to usual grids

Maintained high image similarity with SSIM above 96.6%

Reduced computational costs while preserving image quality

Abstract

Ultrafast imaging modes, such as coherent plane-wave compounding (CPWC), capture a large field of view in a single pulse-echo measurement using parallel receive focusing. The number of foci or, equivalently, the number of volume elements (voxels) in the image determines the computational costs and the memory consumption of the image formation. Herein, 120{\deg} rhombic grids are proposed to specify the voxel positions and reduce the number of voxels in comparison to orthogonal grids. The proposed grids derive from the bivariate sampling theorem and the spectral properties of the images formed by the delay-and-sum algorithm in CPWC. A phantom experiment validated the proposed grids and showed reductions in the number of voxels by 81.4 % and 14.7 % in comparison to the usual and optimal orthogonal grids, respectively. Mean structural similarity indices above 96.6 % and relative root mean-squared errors below 6.8 % confirmed the visual equivalence of all images after interpolations to the usual orthogonal grid.