Improved Impedance Tomography with Hybrid Data

Improved Impedance Tomography with Hybrid Data


How do we improve tomographic imaging methods and get better images, e.g., in medical imaging and materials science? Tomography aims at reconstructing 2D and 3D images of an object's interior from exterior measurements. Due to the underlying physics it is often difficult, using a single tomographic modality, to achieve both high contrast and high resolution images. This project developed new mathematical methods and algorithms for hybrid-data tomography that combine different coupled physical phenomena, e.g., electrical current and acoustic waves, for tomographic reconstructions with enhanced details and contrast. We considered hybrid-data tomography such as acousto-electric tomography, elastography, electrical impedance tomography (EIT), magnetic resonance EIT and photo-acoustic tomography. Fundamental questions related to hybrid-data tomography have been answered successfully, and new algorithms have been formulated and tested on laboratory data.

This research project was funded by grant no. 4002-00123 from the Danish Council for Independent Research | Natural Sciences

The project started July 1, 2014, and ended December 31, 2018. It was located at Department of Applied Mathematics and Computer Science (DTU Compute) at the Technical University of Denmark (DTU).

The Research Team

Principal investigators

All from the Section for Scientific Computing at the Department of Applied Mathematics and Computer Science, DTU

Team members


Highlight activities

Project Outline

This project focuses on coupled-physics impedance tomography with hybrid data. We will derive and compare constructive formulations of the underlying problems, formulate mathematical algorithms for their solution, and rigorously prove fundamental properties of the algorithms and the solutions. In addition, we will develop state-of-the-art numerical reconstruction algorithms for the problems, and we will find ways to incorporate prior information about the solution to obtain regularized reconstruction methods whose solutions are robust w.r.t. to data errors.

We will approach a number of important theoretical questions related to impedance tomography via hybrid data, with focus on CDII and UMEIT problems. These questions are primarily connected to the underlying PDE formulations, the associated variational formulations, and how to impose stability by means of data fitting and prior information. We are not concerned with the problems of building the devices and performing the measurements; for test and validation we will use artificial data created through numerical simulations.

The project has considered the following questions related to tomography problems with hybrid data: