A team from the University of Bremen and University College London, including Maths4DL team members, have won the EIT (Electrical Impedance Tomography) Kuopio Tomography Challenge 2023.
1st place was awarded to Alexander Denker, Zeljko Kereta, Imraj Singh, Riccardo Barbano, Tom Freudenberg, Tobias Kluth and Simon Arridge for their efforts to recover the shapes of 2D targets imaged with electrical impedance tomography, collected in the Electrical Tomography Laboratory at the University of Eastern Finland, Finland.
In electrical impedance tomography, the task involves reconstructing the internal electric conductivity distribution of a physical object. This is achieved through the utilization of measurements taken at the object’s boundary, which encompass electric current and voltage. From a mathematical perspective, the core challenge revolves around deducing a non-negative coefficient for a diffusion equation based on the boundary data consisting of electric current density and potential.
In real measurement setups, the object is imaged using measurement electrodes, which have a finite size and which cover only parts of the object boundary. The significance of this is that the reconstruction must be computed from an incomplete set of boundary data, a highly ill-posed and challenging task.