Bayesian Approach for a Robust Speed-of-Sound Reconstruction Using Pulse-Echo Ultrasound

Stähli, Patrick; Frenz, Martin; Jaeger, Michael

doi:10.1109/tmi.2020.3029286

Cited by 34 publications

(43 citation statements)

References 51 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We use the first transducer element as a source with a Ricker wavelet of 2 MHz center frequency and all transducers as receivers. Our approach predicts traveltimes accurately, even though the frequencies of simulated ultrasonic waves are lower than those used commercially (5)(6)(7)(8)(9)(10)(11)(12). The traveltime modelling presented here is based on the ray theory, which assumes infinite frequencies.…”

Section: Validation With Numerical Simulationsmentioning

confidence: 99%

See 1 more Smart Citation

Ultrasound longitudinal-wave anisotropy estimation in muscle tissue

Martiartu¹,

Simutė²,

Rominger³

et al. 2021

Preprint

View full text Add to dashboard Cite

<p> The velocity of ultrasound longitudinal waves (speed of sound) is emerging as a valuable biomarker for a wide range of diseases, including musculoskeletal disorders. Muscles are fiber-rich tissues that exhibit anisotropic behavior, meaning that velocities vary with the wave-propagation direction. Quantifying anisotropy is therefore essential to improve velocity estimates while providing a new metric that relates to both muscle composition and architecture. This work presents a method to estimate longitudinal-wave anisotropy in transversely isotropic tissues. We assume elliptical anisotropy and consider an experimental setup that includes a flat reflector located in front of the linear probe. Moreover, we consider transducers operating multistatically. This setup allows us to measure first-arrival reflection traveltimes. Unknown muscle parameters are the orientation angle of the anisotropy symmetry axis and the velocities along and across this axis. We derive analytical expressions for the relationship between traveltimes and anisotropy parameters, accounting for reflector inclinations. To analyze the structure of this nonlinear forward problem, we formulate the inversion statistically using the Bayesian framework. Solutions are probability density functions useful for quantifying uncertainties in parameter estimates. Using numerical examples, we demonstrate that all parameters can be well constrained when traveltimes from different reflector inclinations are combined. Results from a wide range of acquisition and medium properties show that uncertainties in velocity estimates are substantially lower than expected velocity differences in muscle. Thus, our formulation could provide accurate muscle anisotropy estimates in future clinical applications.</p> p { margin-bottom: 0.25cm; line-height: 115%; background: transparent }

show abstract

Section: Validation With Numerical Simulationsmentioning

confidence: 99%

“…Speed-of-sound estimation in tissue using ultrasound has attracted considerable attention in recent years [1]- [7]. Speed of sound refers to the propagation velocity of longitudinal waves, which are typically used for image formation in ultrasound systems.…”

Section: Introductionmentioning

confidence: 99%

Ultrasound longitudinal-wave anisotropy estimation in muscle tissue

Martiartu¹,

Simutė²,

Rominger³

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

“…This is practically equivalent to having a virtual receiver that measures time delays between specific wave-propagation paths at every spatial location. So far, CUTE has proven excellent in retrieving correct SoS values with approximately 10 m/s contrast resolution in tissue-mimicking phantoms [27], opening up the prospect of quantitative non-invasive diagnosis with SoS imaging.…”

Section: Introductionmentioning

confidence: 99%

First-in-human diagnostic study of hepatic steatosis with computed ultrasound tomography in echo mode (CUTE)

Stähli

Becchetti

Martiartu

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

Non-alcoholic fatty liver disease is rapidly emerging as the leading global cause of chronic liver disease. Efficient disease management requires low-cost, noninvasive techniques for diagnosing hepatic steatosis accurately. Here we propose quantifying liver speed-of-sound (SoS) with computed US tomography in echo mode (CUTE), a newly developed US imaging modality adapted to clinical pulse-echo systems. CUTE reconstructs the spatial distribution of SoS by measuring local echo phase shifts when probing tissue at different steering angles in transmission and reception. This first-in-human phase II study shows that liver CUTE-SoS estimates correlate strongly (r=-0.84, p=8.27∙10-13) with controlled attenuation parameter values, a commonly used tool for assessing liver steatosis, and have 90.9% (95% confidence interval: 84 - 100%) sensitivity and 95.5% (81 - 100%) specificity for differentiating normal and significantly steatotic livers. Because CUTE offers the same flexibility as conventional US imaging, it can be readily extended to other clinical applications, establishing it as a new quantitative add-on to diagnostic US.

show abstract

“…[5] used spatial phase shifts of beamformed echoes obtained under varying steering angles. One of the problems of this approach is that small variations in the inputs, for instance in the presence of measurement or phase noises can make the setup unstable [6]. Thus, [6] included an a priori model based on B-mode image segmentation in a Bayesian framework.…”

Section: Introductionmentioning

confidence: 99%

“…One of the problems of this approach is that small variations in the inputs, for instance in the presence of measurement or phase noises can make the setup unstable [6]. Thus, [6] included an a priori model based on B-mode image segmentation in a Bayesian framework. This model relies on manual segmentation of the B-mode images which might not be practical in clinical setups.…”

Section: Introductionmentioning

confidence: 99%

AutoSpeed: A Linked Autoencoder Approach for Pulse-Echo Speed-of-Sound Imaging for Medical Ultrasound

Jush¹,

Biele²,

Dueppenbecker³

et al. 2022

Preprint

View full text Add to dashboard Cite

Quantitative ultrasound, e.g., speed-of-sound (SoS) in tissues, provides information about tissue properties that have diagnostic value. Recent studies showed the possibility of extracting SoS information from pulse-echo ultrasound raw data (a.k.a. RF data) using deep neural networks that are fully trained on simulated data. These methods take sensor domain data, i.e., RF data, as input and train a network in an end-to-end fashion to learn the implicit mapping between the RF data domain and SoS domain. However, such networks are prone to overfitting to simulated data which results in poor performance and instability when tested on measured data. We propose a novel method for SoS mapping employing learned representations from two linked autoencoders. We test our approach on simulated and measured data acquired from human breast mimicking phantoms. We show that SoS mapping is possible using linked autoencoders. The proposed method has a Mean Absolute Percentage Error (MAPE) of 2.39% on the simulated data. On the measured data, the predictions of the proposed method are close to the expected values with MAPE of 1.1 %. Compared to an end-to-end trained network, the proposed method shows higher stability and reproducibility.

show abstract

Bayesian Approach for a Robust Speed-of-Sound Reconstruction Using Pulse-Echo Ultrasound

Cited by 34 publications

References 51 publications

Ultrasound longitudinal-wave anisotropy estimation in muscle tissue

Ultrasound longitudinal-wave anisotropy estimation in muscle tissue

First-in-human diagnostic study of hepatic steatosis with computed ultrasound tomography in echo mode (CUTE)

AutoSpeed: A Linked Autoencoder Approach for Pulse-Echo Speed-of-Sound Imaging for Medical Ultrasound

Contact Info

Product

Resources

About