In this article, we consider deep learning strategies in ultrasound systems, from the front end
to advanced applications. Our goal is to provide the reader with a broad understanding of …

Inverse problems in image processing are typically cast as optimization tasks, consisting of
data fidelity and stabilizing regularization terms. A recent regularization strategy of great …

The standard technique used by commercial medical ultrasound systems to form B-mode
images is delay and sum (DAS) beamforming. However, DAS often results in limited image …

Sparse sensor arrays have attracted considerable attention in various fields such as radar,
array processing, ultrasound imaging and communications. In the context of correlation …

Ultrasound image reconstruction can be approximately cast as a linear inverse problem that
has traditionally been solved with penalized optimization using the l 1 or l 2 norm, or wavelet …

High-frame-rate ultrasound imaging uses unfocused transmissions to insonify an entire
imaging view for each transmit event, thereby enabling frame rates over 1000 frames per …

Implementation of a high-frequency ultrasound (HFUS) beamformer is computationally
challenging because of its high sampling rate. This article introduces an efficient …

The most common technique for generating B-mode ultrasound (US) images is delay-and-
sum (DAS) beamforming, where the signals received at the transducer array are sampled …

Efficient ultrasound (US) systems that produce high-quality images can improve current
clinical diagnosis capabilities by making the imaging process much more affordable and …

B-mode images undergo degradation in the boundary region because of the limited number
of elements in the ultrasound probe. Herein, a deep learning-based extended aperture …