Unrolled Optimization via Physics-Assisted Convolutional Neural Network for MR-Based Electrical Properties Tomography: A Numerical Investigation
Magnetic Resonance imaging based Electrical Properties Tomography (MR-EPT) is a non-invasive technique that measures the electrical properties (EPs) of biological tissues. In this work, we present and numerically investigate the performance of an unrolled, physics-assisted method for 2D MR-EPT recon...
Saved in:
| Main Authors: | Sabrina Zumbo, Stefano Mandija, Ettore F. Meliado, Peter Stijnman, Thierry G. Meerbothe, Cornelis A.T. van den Berg, Tommaso Isernia, Martina T. Bevacqua |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2024-01-01
|
| Series: | IEEE Open Journal of Engineering in Medicine and Biology |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10534835/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Semantic–Electromagnetic Inversion With Pretrained Multimodal Generative Model
by: Yanjin Chen, et al.
Published: (2024-11-01) -
Data-driven and physics-constrained acoustic holography based on optimizer unrolling
by: Pagavino Manuel, et al.
Published: (2025-01-01) -
Microemulsion dispersion of sulfuric acid in a hydrocarbon medium
by: B. V. Pokidko, et al.
Published: (2014-12-01) -
Identification of Physical Parameters of a Porous Material Located in a Duct by Inverse Methods
by: Marwa KANI, et al.
Published: (2021-12-01) -
The Near-Surface Vertical Variability of Aerosol Single-Scattering Properties over Warsaw: Case Study
by: Michał T. Chiliński, et al.
Published: (2025-04-01)