Learnable Regularization via Padé Activation Units for Flexible Model-Based Beamforming
Author:
Affiliation:
1. Vanderbilt University,Department of Biomedical Engineering,Nashville,TN,USA
2. Eindhoven University of Technology,Department of Electrical Engineering,Eindhoven,Netherlands
Funder
NIH
NAVSEA
NSF
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9957114/9957143/09958768.pdf?arnumber=9958768
Reference18 articles.
1. Performing aperture domain model image reconstruction (ADMIRE) using a deep neural net-work sparse encoder;khan;2021 IEEE International Ultrasonics Symposium (IUS),2021
2. Unfolding Model-Based Beamforming for High Quality Ultrasound Imaging
3. Padé Activation Units: End-to-end Learning of Flexible Activation Functions in Deep Net-works;molina;ArXiv Preprint,2019
4. FIELD: A program for simulating ultrasound systems;jensen;Proc 10th Nordic-Baltic Conf Biomed Imag,1996
5. Calculation of pressure fields from arbitrarily shaped, apodized, and excited ultrasound transducers
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