Correction of concentrated and distributed aberrations in medical ultrasound imaging

A method is presented for iterative correction of wave fields aberrated in a plane located at an arbitrary distance from an array transducer. The signals received from the transducer are processed by an inverse extrapolator in such a way that the output yields the transducer signals as if the transducer had been located directly at the position of the aberrator. For subsequent transmission cycles, the same inverse extrapolator is applied to delta pulses at time instants incorporating the time-reversed estimated aberration profile. The method can be applied to scattering and absorptive media, i.e. in medical conditions. The compensation of distributed aberration is also developed. It is shown that correction algorithms intended for concentrated aberrations can be used to reduce effects due to distributed aberrations; our conclusions with respect to the position of the equivalent concentrated aberrator differ from results reported in the literature. The method is demonstrated on realistic simulations of solid lesions, and cysts (voids) disturbed by intervening aberrating medi

Forward model for quantitative pulse-echo speed-of-sound imaging

Computed ultrasound tomography in echo mode (CUTE) allows determining the spatial distribution of speed-of-sound (SoS) inside tissue using handheld pulse-echo ultrasound (US). This technique is based on measuring the changing phase of beamformed echoes obtained under varying transmit (Tx) and/or receive (Rx) steering angles. The SoS is reconstructed by inverting a forward model describing how the spatial distribution of SoS is related to the spatial distribution of the echo phase shift. CUTE holds promise as a novel diagnostic modality that complements conventional US in a single, real-time handheld system. Here we demonstrate that, in order to obtain robust quantitative results, the forward model must contain two features that were not taken into account so far: a) the phase shift must be detected between pairs of Tx and Rx angles that are centred around a set of common mid-angles, and b) it must account for an additional phase shift induced by the error of the reconstructed position of echoes. In a phantom study mimicking liver imaging, this new model leads to a substantially improved quantitative SoS reconstruction compared to the model that has been used so far. The importance of the new model as a prerequisite for an accurate diagnosis is corroborated in preliminary volunteer results

Full modelling of high-intensity focused ultrasound and thermal heating in the kidney using realistic patient models

Objective: High-intensity focused ultrasound (HIFU) therapy can be used for non-invasive treatment of kidney (renal) cancer, but the clinical outcomes have been variable. In this study, the efficacy of renal HIFU therapy was studied using nonlinear acoustic and thermal simulations in three patients. Methods: The acoustic simulations were conducted with and without refraction in order to investigate its effect on the shape, size and pressure distribution at the focus. The values for the attenuation, sound speed, perfusion and thermal conductivity of the kidney were varied over the reported ranges to determine the effect of variability on heating. Furthermore, the phase aberration was studied in order to quantify the underlying phase shifts using a second order polynomial function. Results: The ultrasound field intensity was found to drop on average 11.1 dB with refraction and 6.4 dB without refraction. Reflection at tissue interfaces was found to result in a loss less than 0.1 dB. Focal point splitting due to refraction significantly reduced the heating efficacy. Perfusion did not have a large effect on heating during short sonication durations. Small changes in temperature were seen with varying attenuation and thermal conductivity, but no visible changes were present with sound speed variations. The aberration study revealed an underlying trend in the spatial distribution of the phase shifts. Conclusion: The results show that the efficacy of HIFU therapy in the kidney could be improved with aberration correction. Significance: A method is proposed by which patient specific pre-treatment calculations could be used to overcome the aberration and therefore make ultrasound treatment possible.Comment: Journal paper, IEEE Transactions on Biomedical Engineering (2018

Phase Aberration Correction: A Deep Learning-Based Aberration to Aberration Approach

One of the primary sources of suboptimal image quality in ultrasound imaging is phase aberration. It is caused by spatial changes in sound speed over a heterogeneous medium, which disturbs the transmitted waves and prevents coherent summation of echo signals. Obtaining non-aberrated ground truths in real-world scenarios can be extremely challenging, if not impossible. This challenge hinders training of deep learning-based techniques' performance due to the presence of domain shift between simulated and experimental data. Here, for the first time, we propose a deep learning-based method that does not require ground truth to correct the phase aberration problem, and as such, can be directly trained on real data. We train a network wherein both the input and target output are randomly aberrated radio frequency (RF) data. Moreover, we demonstrate that a conventional loss function such as mean square error is inadequate for training such a network to achieve optimal performance. Instead, we propose an adaptive mixed loss function that employs both B-mode and RF data, resulting in more efficient convergence and enhanced performance. Finally, we publicly release our dataset, including 161,701 single plane-wave images (RF data). This dataset serves to mitigate the data scarcity problem in the development of deep learning-based techniques for phase aberration correction.Comment: arXiv admin note: text overlap with arXiv:2303.0574

Ultrasound Matrix Imaging. I. The focused reflection matrix and the F-factor

This is the first article in a series of two dealing with a matrix approach \alex{for} aberration quantification and correction in ultrasound imaging. Advanced synthetic beamforming relies on a double focusing operation at transmission and reception on each point of the medium. Ultrasound matrix imaging (UMI) consists in decoupling the location of these transmitted and received focal spots. The response between those virtual transducers form the so-called focused reflection matrix that actually contains much more information than a raw ultrasound image. In this paper, a time-frequency analysis of this matrix is performed, which highlights the single and multiple scattering contributions as well as the impact of aberrations in the monochromatic and broadband regimes. Interestingly, this analysis enables the measurement of the incoherent input-output point spread function at any pixel of this image. A focusing criterion can then be built, and its evolution used to quantify the amount of aberration throughout the ultrasound image. In contrast to the standard coherence factor used in the literature, this new indicator is robust to multiple scattering and electronic noise, thereby providing a highly contrasted map of the focusing quality. As a proof-of-concept, UMI is applied here to the in-vivo study of a human calf, but it can be extended to any kind of ultrasound diagnosis or non-destructive evaluation.Comment: 14 pages, 3 figure