Determining anisotropic conductivity using diffusion tensor imaging data in magneto-acoustic tomography with magnetic induction

Habib Ammari, Lingyun Qiu, Fadil Santosa, Wenlong Zhang

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

In this paper we present a mathematical and numerical framework for a procedure of imaging anisotropic electrical conductivity tensor by integrating magneto-acoutic tomography with data acquired from diffusion tensor imaging. Magneto-acoustic tomography with magnetic induction (MAT-MI) is a hybrid, non-invasive medical imaging technique to produce conductivity images with improved spatial resolution and accuracy. Diffusion tensor imaging (DTI) is also a non-invasive technique for characterizing the diffusion properties of water molecules in tissues. We propose a model for anisotropic conductivity in which the conductivity is proportional to the diffusion tensor. Under this assumption, we propose an optimal control approach for reconstructing the anisotropic electrical conductivity tensor. We prove convergence and Lipschitz type stability of the algorithm and present numerical examples to illustrate its accuracy and feasibility.

Original languageEnglish (US)
Article number125006
JournalInverse Problems
Volume33
Issue number12
DOIs
StatePublished - Nov 10 2017

Bibliographical note

Publisher Copyright:
© 2017 IOP Publishing Ltd.

Keywords

  • anisotropic conductivity
  • diffusion tensor imaging
  • hybrid imaging
  • magneto-acoustic tomography with magnetic induction

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