In the realm of 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.
The purpose of the challenge is 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. Detailed descriptions of the experimental setup, targets, and measurement protocol can be found in the Data section.
The outcome of the challenge should be an algorithm which takes in the EIT data, and it's associated metadata about the measurement geometry, and produces a reconstruction which has been segmented into three components: water, resistive inclusions, and conductive inclusions.
| Mikko Räsänen | University of Eastern Finland, Finland |
| Petri Kuusela | University of Eastern Finland, Finland |
| Jyrki Jauhiainen | University of Helsinki, Finland |
| Muhammad Ziaul Arif | University of Eastern Finland, Finland |
| Kenneth Scheel | University of Eastern Finland, Finland |
| Tuomo Savolainen | University of Eastern Finland, Finland |
| Aku Seppänen | University of Eastern Finland, Finland |
