Reconstruction Algorithms for EIT
Next generation of Electrotomographic Imaging
Description
Electrical impedance tomography (EIT) is a radiation-free and non-destructive method for determining the conductivity field of an object. A weak electric current is passed through the object via multiple electrodes attached to the surface, while the distribution of the electrical potential on the surface is measured. The three-dimensional conductivity field can be derived from these measurements in a reconstruction step. As no radiation is used and no sensors need to be inserted into the object, EIT is used in both medical and industrial imaging. The method is particularly suitable for observing and monitoring two-phase pipe flows that occur under extreme conditions such as high pressure, temperature and flow velocities, as the measurement volume does not need to be instrumented.
The aim of the “ROBIN” project is to use EIT to investigate the flows in power plant cooling water pipes. Depending on the operating status, different flow states of steam and water can occur there, which allow conclusions to be drawn about the operating status of the power plant. In order to precisely record these states, we want to develop the next generation of electrotomographic imaging, which offers a high temporal and spatial resolution.
A central problem is the reconstruction of the conductivity field, as this is an ill-posed problem for which no clear mathematical solution exists. Two approaches are being pursued as part of the project: An algorithmic approach that uses regularization techniques to provide a solution to the boundary value problem, and an approach based on pre-trained artificial intelligence that proposes a plausible conductivity field.
Tasks
- In-depth study of the underlying mathematical problem of EIT.
- Investigate and compare different approaches to the solution, including analytical methods and machine learning.
- Design an algorithm to reconstruct volumetric data based on EIT measurements.
- Implementation of the reconstruction algorithm in C++ or a comparable programming language and subsequent validation of the results.
- Development of a software interface to the existing measurement system to enable real-time imaging.
Profile
- Completed Master’s degree in physics, mathematics, engineering or a comparable field.
- Experience in the development of algorithms, especially in image reconstruction and analysis, and machine learning using Python, Matlab or C++.
- Good knowledge of the physical principles and technologies of electrical impedance tomography (EIT) and experience in modeling electrical properties.
- Strong ability to solve complex problems and present solutions in a clear, concise and well-documented manner.
- Knowledge of EIT-specific software tools such as EIDORS, GREIT or FEMM is an advantage.
We offer
- Fully funded PhD position
- Development opportunities for the implementation of new ideas
- Flexible working hours
- Barrier-free office building
If you would like to take on a responsible role in researching this new method as a PhD student, then apply now and bring your expertise to our team! Please send your detailed application or questions with the subject “ROBIN” to:
Dr. Achim Sack, mss-recruitment@fau.de
Your application must include: CV, certificates and a letter of motivation outlining your interests, research background and suitability for the advertised position.