Deep-Learning Based Adaptive Ultrasound Imaging From Sub-Nyquist Channel Data-Reference-Cited by-同舟云学术

Deep-Learning Based Adaptive Ultrasound Imaging From Sub-Nyquist Channel Data

Published:2022-05 Issue:5 Volume:69 Page:1638-1648
ISSN:0885-3010
Container-title:IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control
language:
Short-container-title:IEEE Trans. Ultrason., Ferroelect., Freq. Contr.

Author:

Mamistvalov Alon¹^ORCID,Amar Ariel¹^ORCID,Kessler Naama¹^ORCID,Eldar Yonina C.¹^ORCID

Affiliation:

1. Faculty of Mathematics and Computer Science, Weizmann Institute of Science, Rehovot, Israel

Funder

Igel Manya Center for Biomedical Engineering and Signal Processing as well as the Benoziyo Endowment Fund for the Advancement of Science, the Estate of Olga Klein—Astrachan

European Union’s Horizon 2020 Research and Innovation Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Acoustics and Ultrasonics,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/58/9763860/09738614.pdf?arnumber=9738614

Reference49 articles.

1. Deep CNN-Based Ultrasound Super-Resolution for High-Speed High-Resolution B-Mode Imaging

2. A Generative Adversarial Neural Network for Beamforming Ultrasound Images : Invited Presentation

3. High-Quality Plane Wave Compounding Using Convolutional Neural Networks

4. High Frame-Rate Ultrasound Imaging Using Deep Learning Beamforming

5. Efficient B-Mode Ultrasound Image Reconstruction From Sub-Sampled RF Data Using Deep Learning

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