Jointly learning selection matrices for transmitters, receivers and fourier coefficients in multichannel imaging

H Wang, Y Zhou, E Pérez… - ICASSP 2024-2024 IEEE …, 2024 - ieeexplore.ieee.org
Strategic subsampling has become a focal point due to its effectiveness in compressing
data, particularly in the Full Matrix Capture (FMC) approach in ultrasonic imaging. This …

Dehazing ultrasound using diffusion models

TSW Stevens, FC Meral, J Yu… - … on Medical Imaging, 2024 - ieeexplore.ieee.org
Echocardiography has been a prominent tool for the diagnosis of cardiac disease. However,
these diagnoses can be heavily impeded by poor image quality. Acoustic clutter emerges …

Ultrasound viscoelastography by acoustic radiation force: A state-of-the-art review

X Chen, X Li, S Turco, RJG Van Sloun… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Ultrasound elastography (USE) is a promising tool for tissue characterization as several
diseases result in alterations of tissue structure and composition, which manifest as changes …

A survey on deep learning in medical ultrasound imaging

K Song, J Feng, D Chen - Frontiers in Physics, 2024 - frontiersin.org
Ultrasound imaging has a history of several decades. With its non-invasive, low-cost
advantages, this technology has been widely used in medicine and there have been many …

Integrating AI in NDE: Techniques, Trends, and Further Directions

E Pérez, CE Ardic, O Çakıroğlu, K Jacob… - arXiv preprint arXiv …, 2024 - arxiv.org
The digital transformation is fundamentally changing our industries, affecting planning,
execution as well as monitoring of production processes in a wide range of application …

Hardware-Independent Deep Signal Processing: A Feasibility Study in Echocardiography

EL Gundersen, E Smistad, TS Jahren… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Deep learning (DL) models have emerged as alternative methods to conventional
ultrasound (US) signal processing, offering the potential to mimic signal processing chains …

Boosting Cardiac Color Doppler Frame Rates with Deep Learning

J Puig, D Friboulet, HJ Ling, F Varray… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
Color Doppler echocardiography enables visualization of blood flow within the heart.
However, the limited frame rate impedes the quantitative assessment of blood velocity …

[HTML][HTML] Development of a Deep Learning–Based System for Optic Nerve Characterization in Transorbital Ultrasound Images on a Multicenter Data Set

F Marzola, P Lochner, A Naldi, R Lemor… - Ultrasound in Medicine …, 2023 - Elsevier
Objective Characterization of the optic nerve through measurement of optic nerve diameter
(OND) and optic nerve sheath diameter (ONSD) using transorbital sonography (TOS) has …

Automatic Quantitative Assessment of Muscle Strength Based on Deep Learning and Ultrasound

X Yang, B Zhang, Y Liu, Q Lv, J Guo - Ultrasonic Imaging, 2024 - journals.sagepub.com
Skeletal muscle is a vital organ that promotes human movement and maintains posture.
Accurate assessment of muscle strength is helpful to provide valuable insights for athletes' …

A Deep Learning Approach for Beamforming and Contrast Enhancement of Ultrasound Images in Monostatic Synthetic Aperture Imaging: A Proof-of-Concept

E Bosco, E Spairani, E Toffali, V Meacci… - IEEE Open Journal …, 2024 - ieeexplore.ieee.org
Goal: In this study, we demonstrate that a deep neural network (DNN) can be trained to
reconstruct high-contrast images, resembling those produced by the multistatic Synthetic …