Magnetic Resonance-Based Electric Properties Tomography via Green's Integral Identity

A new approach to Magnetic Resonance-based Electric Properties Tomography (EPT) is presented. The method applies Green's integral identity to the equation that regulates the EPT problem. The resultant integral equations are used to impose the consistency of the measured values of the radiofrequ...

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Bibliographic Details
Published in:IEEE access Vol. 13; pp. 42029 - 42044
Main Authors: Zilberti, Luca, Arduino, Alessandro, Zanovello, Umberto, Martinez, Jessica A., Moulin, Kevin, Troia, Adriano, Bottauscio, Oriano
Format: Journal Article
Language:English
Published: Piscataway IEEE 2025
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Conductivity
Data acquisition
Dielectric properties
Dielectrics
Electric properties
electric properties tomography (EPT)
Fitting
Green identity
Integral equations
Kernel
Magnetic properties
Magnetic resonance
Magnetic resonance imaging
magnetic resonance imaging (MRI)
Mathematical models
Noise
Radio frequency
Synthetic data
Tomography
Trustworthiness
ISSN:2169-3536, 2169-3536
Online Access:Get full text
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Summary:A new approach to Magnetic Resonance-based Electric Properties Tomography (EPT) is presented. The method applies Green's integral identity to the equation that regulates the EPT problem. The resultant integral equations are used to impose the consistency of the measured values of the radiofrequency field. This is achieved by seeking dielectric properties values that allow satisfying the identity within suitable kernels of voxels. In each kernel, an overdetermined system of equations is written, and the corresponding problem is solved in the least squares sense, providing an index of trustworthiness of the solution. Both the complete formulation and its phase-based approximation are presented. The application of a filter, which post-processes the raw results based on the index of trustworthiness, is also discussed. The performance of the method is evaluated on synthetic data and experimental measurements acquired on a heterogeneous brain phantom and on four human volunteers. The reconstructions are compared to those produced through a Helmholtz-EPT with adaptive kernel. The new EPT method performs well in all tests.
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ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2025.3546036