The Impact of Model-Based Clutter Suppression on Cluttered, Aberrated Wavefronts

Abstract

Recent studies reveal that both phase aberration and reverberation play a major role in degrading ultrasound image quality. We previously developed an algorithm for suppressing clutter, but we have not yet tested it in the context of aberrated wavefronts. In this study, we evaluate our previously reported algorithm, called aperture domain model image reconstruction (ADMIRE), in the presence of phase aberration and in the presence of multipath scattering and phase aberration. We use simulations to investigate phase aberration corruption and correction in the presence of reverberation. As part of this study, we observed that ADMIRE leads to suppressed levels of aberration. In order to accurately characterize aberrated signals of interest, we introduced an adaptive component to ADMIRE to account for aberration, referred to as adaptive ADMIRE. We then use ADMIRE, adaptive ADMIRE and conventional filtering methods to characterize aberration profiles on in vivo liver data. These in vivo results suggest adaptive ADMIRE could be used to better characterize a wider range of aberrated wavefronts. The aberration profiles’ FWHM of ADMIRE, adaptive ADMIRE and post-filtered data with 0.4 mm−1 spatial cutoff frequency are 4.0 ± 0.28 mm, 2.8 ± 1.3 mm and 2.8 ± 0.57 mm, respectively, while the average RMS values in the same order are 16 ± 5.4 ns, 20 ± 6.3 ns and 19 ± 3.9 ns, respectively. Finally, because ADMIRE suppresses aberration, we perform a limited evaluation of image quality using simulations and in vivo data to determine how ADMIRE and adaptive ADMIRE perform with and without aberration correction.

A Robust Method for Ultrasound Beamforming in the Presence of Off-Axis Clutter and Sound Speed Variation

“…The parameter of α adjusts the relative weight of L1 and L2 norms between 0 and 1. The degrees of freedom ( df ), which are a function of λ , reported by Tibshirani et al [34], play a crucial role in the performance of ADMIRE [29, 30, 35].…”

“…Our group introduced a model-based beamforming algorithm [8, 27, 28, 29, 30]. The algorithm uses a model of received wavefronts on aperture domain signals reflected from scatterers located in the imaging field of interest.…”

Advances in ultrasonography: image formation and quality assessment

“…The harmonic imaging approach significantly reduces clutter signals, but clutter signals are still not eliminated perfectly. Byram et al proposed a method, called aperture domain model image reconstruction (ADMIRE), for reduction of clutter signals contained in channel echo signals [ 52 – 54 ]. In their method, a model of the channel echo signal is expressed as where , , and are the lateral position in the aperture, time, and angular frequency, respectively, is the wavenumber, and are the lateral and axial positions of a scatterer at time , respectively, is the time delay of the wavefront of a signal arriving from a point, which is located at lateral and axial positions of and , respectively, at time , is the number of scatterers, and is the amplitude modulation induced by windowing in Fourier transform and element directivity.…”

GENRE (GPU Elastic-Net REgression): A CUDA-Accelerated Package for Massively Parallel Linear Regression with Elastic-Net Regularization

“…However, they often do not address the case in which there is a need to perform many model fits in parallel. For example, the research project that laid the foundation for GENRE involved performing ultrasound image reconstruction using an algorithm called Aperture Domain Model Image REconstruction (ADMIRE) (Byram, Dei, Tierney, & Dumont, 2015;Byram & Jakovljevic, 2014;Dei & Byram, 2017). This algorithm is computationally expensive due to the fact that in one stage, it requires thousands of instances of linear regression with elastic-net regularization to be performed in order to fit models of ultrasound data.…”