Correlation of RF signals during angular compounding

Abstract

A theoretical analysis of the correlation between radio-frequency (RF) echo signal data acquired from the same location but at different angles is presented. The accuracy of the theoretical results is verified with computer simulations. Refinements to previous analyses of the correlation of RF signals originating from the same spatial location at different angular positions are made. We extend the analysis to study correlation of RF signals coming from different spatial locations and eventually correlation of RF signal segments that intersect at the same spatial location. The theory predicts a faster decorrelation with a change in the insonification angle for longer RF echo signal segments. As the RF signal segment becomes shorter, the decorrelation rate with angle is slower and approaches the limit corresponding to the correlation of RF signals originating from the same spatial location. Theoretical results provide a clear understanding of angular compounding techniques used to improve the signal-to-noise ratio in ultrasonic parametric imaging and in elastography.

Spatial Angular Compounding Technique for H-Scan Ultrasound Imaging

“…We hypothesize that because we limited all steered plane wave transmissions to the ±18° range, increasing the number of steered plane wave images within that space increases the correlation between the images to be averaged. Spatial compounding is most effective when signals to be averaged are uncorrelated (Chen et al 2005). Notwithstanding, when ultrasound scatterers are densely distributed and of sufficient number, the RF backscattered signals obey Gaussian statistics while the envelope of the signal follows a Rayleigh distribution (Wagner et al 1988).…”

Normal and shear strain imaging using 2D deformation tracking on beam steered linear array datasets

“…Quantitative experimental results with spatial angular compounding demonstrate that least-squares compounding provides significant improvement in the SNR e and CNR e , when compared to weighted-compounding. 11 Chen and Varghese 26 extended the least-squares approach by incorporating a crosscorrelation matrix of displacement noise errors into the strain estimation process thereby avoiding any other assumptions for simplifying estimation noise. In addition, angular compounding has been used to estimate variations in attenuation to reduce shadowing of spatially compounded images 31 and for Young's modulus 32 reconstructions.…”

“…11-15, 21, 26-30 Our group has developed novel approaches that utilize angular displacements estimated from beam-steered RF echo data pairs to improve accuracy of the estimated lateral displacement vector. 13,15,26 Based on the assumption that noise artifacts are independent and identically distributed, Techavipoo et al 27,28 developed a least-squares approach to estimate both normal and shear strain tensors using RF data acquired with phased array transducers. Rao et al 12,29 modified this approach for linear array transducers using 1D cross-correlation based analysis.…”