Deep-learning-based tomographic imaging is an important application of artificial
intelligence and a new frontier of machine learning. Deep learning has been widely used in …

Abstract Delay-and-sum (DAS) is the most widespread digital beamformer in high-frame-rate
ultrasound imaging. Its implementation is simple and compatible with real-time applications …

In recent years, many studies have examined filters for eliminating or reducing speckle
noise, which is inherent to ultrasound images, in order to improve the metrological …

Biomedical imaging is unequivocally dependent on the ability to reconstruct interpretable
and high-quality images from acquired sensor data. This reconstruction process is pivotal …

We investigate the use of deep neural networks (DNNs) for suppressing off-axis scattering in
ultrasound channel data. Our implementation operates in the frequency domain via the short …

Image reconstruction from radio-frequency (RF) data is crucial for ultrafast plane wave
ultrasound (PWUS) imaging. Compared with the traditional delay-and-sum (DAS) method …

Single plane wave transmissions are promising for automated imaging tasks requiring high
ultrasound frame rates over an extended field of view. However, a single plane wave …

By localizing microbubbles (MBs) in the vasculature, ultrasound localization microscopy
(ULM) has recently been proposed, which greatly improves the spatial resolution of …

In ultrasound (US) imaging, various types of adaptive beamforming techniques have been
investigated to improve the resolution and the contrast-to-noise ratio of the delay and sum …

Ultrasound imaging is widely used in medical diagnosis. It has the advantages of being
performed in real time, cost-efficient, noninvasive, and nonionizing. The traditional delay …