Literature DB >> 26302510

An Inverse Problems Approach to MR-EPT Image Reconstruction.

A Borsic, I Perreard, A Mahara, R J Halter.   

Abstract

Magnetic Resonance-Electrical Properties Tomography (MR-EPT) is an imaging modality that maps the spatial distribution of the electrical conductivity and permittivity using standard MRI systems. The presence of a body within the scanner alters the RF field, and by mapping these alterations it is possible to recover the electrical properties. The field is time-harmonic, and can be described by the Helmholtz equation. Approximations to this equation have been previously used to estimate conductivity and permittivity in terms of first or second derivatives of RF field data. Using these same approximations, an inverse approach to solving the MR-EPT problem is presented here that leverages a forward model for describing the magnitude and phase of the field within the imaging domain, and a fitting approach for estimating the electrical properties distribution. The advantages of this approach are that 1) differentiation of the measured data is not required, thus reducing noise sensitivity, and 2) different regularization schemes can be adopted, depending on prior knowledge of the distribution of conductivity or permittivity, leading to improved image quality. To demonstrate the developed approach, both Quadratic (QR) and Total Variation (TV) regularization methods were implemented and evaluated through numerical simulation and experimentally acquired data. The proposed inverse approach to MR-EPT reconstruction correctly identifies contrasts and accurately reconstructs the geometry in both simulations and experiments. The TV regularized scheme reconstructs sharp spatial transitions, which are difficult to reconstruct with other, more traditional approaches.

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Year:  2015        PMID: 26302510     DOI: 10.1109/TMI.2015.2466082

Source DB:  PubMed          Journal:  IEEE Trans Med Imaging        ISSN: 0278-0062            Impact factor:   10.048


  4 in total

1.  Brain Tissue Conductivity Measurements with MR-Electrical Properties Tomography: An In Vivo Study.

Authors:  Stefano Mandija; Petar I Petrov; Jord J T Vink; Sebastian F W Neggers; Cornelis A T van den Berg
Journal:  Brain Topogr       Date:  2020-12-08       Impact factor: 3.020

2.  Magnetic resonance electrical property mapping at 21.1 T: a study of conductivity and permittivity in phantoms, ex vivo tissue and in vivo ischemia.

Authors:  Ghoncheh Amouzandeh; Frederic Mentink-Vigier; Shannon Helsper; F Andrew Bagdasarian; Jens T Rosenberg; Samuel C Grant
Journal:  Phys Med Biol       Date:  2020-02-28       Impact factor: 3.609

3.  Electrical Properties Tomography Based on $B_{{1}}$ Maps in MRI: Principles, Applications, and Challenges.

Authors:  Jiaen Liu; Yicun Wang; Ulrich Katscher; Bin He
Journal:  IEEE Trans Biomed Eng       Date:  2017-08-21       Impact factor: 4.538

4.  Opening a new window on MR-based Electrical Properties Tomography with deep learning.

Authors:  Stefano Mandija; Ettore F Meliadò; Niek R F Huttinga; Peter R Luijten; Cornelis A T van den Berg
Journal:  Sci Rep       Date:  2019-06-20       Impact factor: 4.379

  4 in total

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