A joint three-plane physics-constrained deep learning based polynomial fitting approach for MR electrical properties tomography

A joint three-plane physics-constrained deep learning based polynomial fitting approach for MR electrical properties tomography

Magnetic resonance electrical properties tomography can extract the electrical properties of in-vivo tissue. To estimate tissue electrical properties, various reconstruction algorithms have been proposed. However, physics-based reconstructions are prone to various artifacts such as noise amplificati...

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Bibliographic Details
Main Authors: Kyu-Jin Jung, Thierry G. Meerbothe, Chuanjiang Cui, Mina Park, Cornelis A.T. van den Berg, Stefano Mandija, Dong-Hyun Kim
Format: Article
Language:English
Published: Elsevier 2025-02-01
Series:NeuroImage
Subjects:
Electrical properties tomography
Conductivity neuroimaging
Phase-based conductivity reconstruction
MR image synthetization
Physics-constrained neural network
Deep learning
Online Access:http://www.sciencedirect.com/science/article/pii/S1053811925000564
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http://www.sciencedirect.com/science/article/pii/S1053811925000564

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