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Prior-knowledge based iterative reconstruction for terahertz tomography.

Terahertz (THz) tomography is an up and coming technology that uses electromagnetic radiation with terahertz frequency for tomographic imaging. Like X-rays, THz waves can give information about the interior of an object through interaction with the object. In contrast to X-rays, there are no known negative effects of THz waves, making their application attractive for biomedical purposes as well as industrial inspection. THz rays interact with many materials in different ways. They are absorbed in polar materials such as water, penetrate most packing materials (plastic, paper, ceramics, …) and are completely reflected by metal. With terahertz tomography it is possible to, for instance visualize the contents of a sealed package. The Gaussian THz beam however, diverges much faster than an X-ray beam and reflection and refraction effects play a dominant role, preventing the use of X-ray reconstruction techniques. Here, we focus on the development of prior-knowledge based iterative reconstruction techniques for pulsed terahertz tomographic data that not only provides information on the absorption but also on phase differences.
Date:1 Oct 2019 →  30 Sep 2023
Disciplines:Modelling and simulation, Signal processing not elsewhere classified