Unrolled Optimization via Physics-Assisted Convolutional Neural Network for MR-Based Electrical Properties Tomography: A Numerical Investigation-Reference-Cited by-同舟云学术

Unrolled Optimization via Physics-Assisted Convolutional Neural Network for MR-Based Electrical Properties Tomography: A Numerical Investigation

Published:2024 Issue: Volume:5 Page:505-513
ISSN:2644-1276
Container-title:IEEE Open Journal of Engineering in Medicine and Biology
language:
Short-container-title:IEEE Open J. Eng. Med. Biol.

Author:

Zumbo Sabrina¹,Mandija Stefano²^ORCID,Meliadò Ettore F.³^ORCID,Stijnman Peter²^ORCID,Meerbothe Thierry G.²^ORCID,van den Berg Cornelis A.T.²^ORCID,Isernia Tommaso¹^ORCID,Bevacqua Martina T.¹^ORCID

Affiliation:

1. Department DIIES, Università Mediterranea di Reggio Calabria, Reggio Calabria, Italy

2. Department of Radiotherapy, Division of Imaging & Oncology, University Medical Center Utrecht, Utrecht, The Netherlands

3. Computational Imaging Group for MR Diagnostics & Therapy, Center for Image Sciences, Utrecht University, Utrecht, The Netherlands

Funder

RADIOAMICA: Open network per la radiomica/radiogenomica cooperativa basata su intelligenza artificiale

DISCERN: aDvanced hybrId breaSt CancER imagiNg

Netherlands Organization for Scientific Research NWO; VENI

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/8782705/10443311/10534835.pdf?arnumber=10534835

Reference45 articles.

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3. Magnetic-Resonance-Based Electrical Properties Tomography: A Review

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5. On conductivity, permittivity, apparent diffusion coefficient, and their usefulness as cancer markers at MRI frequencies