No abstract

Focusing waves inside inhomogeneous media is a fundamental problem for imaging. Spatial variations of wave velocity can strongly distort propagating wave fronts and degrade image quality. Adaptive focusing can compensate for such aberration but is only effective over a restricted field of view. Here, we introduce a full-field approach to wave imaging based on the concept of the distortion matrix. This operator essentially connects any focal point inside the medium with the distortion that a wave front, emitted from that point, experiences due to heterogeneities. A time-reversal analysis of the distortion matrix enables the estimation of the transmission matrix that links each sensor and image voxel. Phase aberrations can then be unscrambled for any point, providing a full-field image of the medium with diffraction-limited resolution. Importantly, this process is particularly efficient in random scattering media, where traditional approaches such as adaptive focusing fail. Here, we first present an experimental proof of concept on a tissue-mimicking phantom and then, apply the method to in vivo imaging of human soft tissues. While introduced here in the context of acoustics, this approach can also be extended to optical microscopy, radar, or seismic imaging.

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 preliminary in vivo result 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.

No abstract