Windowed Radon Transform for Robust Speed-of-Sound Imaging With Pulse-Echo Ultrasound.

In recent years, methods estimating the spatial distribution of tissue speed of sound with pulse-echo ultrasound are gaining considerable traction. They can address limitations of B-mode imaging, for instance in diagnosing fatty liver diseases. Current state-of-the-art methods relate the tissue speed of sound to local echo shifts computed between images that are beamformed using restricted transmit and receive apertures. However, the aperture limitation affects the robustness of phase-shift estimations and, consequently, the accuracy of reconstructed speed-of-sound maps. Here, we propose a method based on the Radon transform of image patches able to estimate local phase shifts from full-aperture images. We validate our technique on simulated, phantom and in-vivo data acquired on a liver and compare it with a state-of-the-art method. We show that the proposed method enhances the stability to changes of beamforming speed of sound and to a reduction of the number of insonifications. In particular, the deployment of pulse-echo speed-of-sound estimation methods onto portable ultrasound devices can be eased by the reduction of the number of insonifications allowed by the proposed method.

Pulse-echo speed-of-sound imaging using convex probes.

Computed ultrasound tomography in echo mode (CUTE) is a new ultrasound (US)-based medical imaging modality with promise for diagnosing various types of disease based on the tissue's speed of sound (SoS). It is developed for conventional pulse-echo US using handheld probes and can thus be implemented in state-of-the-art medical US systems. One promising application is the quantification of the liver fat fraction in fatty liver disease. So far, CUTE was using linear array probes where the imaging depth is comparable to the aperture size. For liver imaging, however, convex probes are preferred since they provide a larger penetration depth and a wider view angle allowing to capture a large area of the liver. With the goal of liver imaging in mind, we adapt CUTE to convex probes, with a special focus on discussing strategies that make use of the convex geometry in order to make our implementation computationally efficient. We then demonstrate in an abdominal imaging phantom that accurate quantitative SoS using convex probes is feasible, in spite of the smaller aperture size in relation to the image area compared to linear arrays. A preliminaryin vivoresult of liver imaging confirms this outcome, but also indicates that deep quantitative imaging in the real liver can be more challenging, probably due to the increased complexity of the tissue compared to phantoms.

3-D Wave-Equation-Based Finite-Frequency Tomography for Ultrasound Computed Tomography.

Ultrasound computed tomography (USCT) has great potential for 3-D quantitative imaging of acoustic breast tissue properties. Typical devices include high-frequency transducers, which makes tomography techniques based on numerical wave propagation simulations computationally challenging, especially in 3-D. Therefore, despite the finite-frequency nature of ultrasonic waves, ray-theoretical approaches to transmission tomography are still widely used. This article introduces a finite-frequency traveltime tomography to medical ultrasound. In addition to being computationally tractable for 3-D imaging at high frequencies, the method has two main advantages: 1) it correctly accounts for the frequency dependence and volumetric sensitivity of traveltime measurements, which are related to off-ray-path scattering and diffraction. 2) It naturally enables out-of-plane imaging and the construction of 3-D images from 2-D slice-by-slice acquisition systems. Our method rests on the availability of calibration data in water, used to linearize the forward problem and to provide analytical expressions of cross correlation traveltime sensitivity. As a consequence of the finite-frequency content, sensitivity is distributed in multiple Fresnel volumes, thereby providing out-of-plane sensitivity. To improve computational efficiency, we develop a memory-efficient implementation by encoding the Jacobian operator with a 1-D parameterization, which allows us to extend the method to large-scale domains. We validate our tomographic approach using laboratory measurements collected with a 2-D setup of transducers and using a cylindrically symmetric phantom. We then demonstrate its applicability for 3-D reconstructions by simulating a slice-by-slice acquisition system using the same data set.