A new approach for image reconstruction in THz computed tomography (THz-CT) is presented. Based on a geometrical optics model containing the THz signal amplitude and phase, a novel algorithm for extracting an average phase from the measured THz signals is derived. Applying the algorithm results in a phase-contrast sinogram, which is further used for image reconstruction. For experimental validation, a fast THz time-domain spectrometer (THz-TDS) in transmission geometry is employed, enabling CT measurements within several minutes. Quantitative evaluation of reconstructed 3D printed plastic profiles reveals the potential of our approach in non-destructive testing of plastic profiles.

The principles of algebraic image reconstruction are applied to THz computed tomography (THz-CT) in order to account for refraction within the sample. Using the nominal sample geometry as a priori knowledge, a highly accurate and robust image reconstruction algorithm based on the physics of geometric optics is presented. The validity of the geometric forward model is verified by a numerical simulation of Maxwell’s equations. Furthermore, the developed method is experimentally tested using measurements performed with a fast THz-CT system based on a THz time-domain spectrometer in transmission mode. Automated evaluations of the reconstructed sample cross sections showed an accuracy of <150 μm.

In this paper, we consider the imaging problem of terahertz (THz) tomography, in particular as it appears in non-destructive testing. We derive a nonlinear mathematical model describing a full THz tomography experiment, and consider linear approximations connecting THz tomography with standard computerized tomography and the Radon transform. Based on the derived models we propose different reconstruction approaches for solving the THz tomography problem, which we then compare on experimental data obtained from THz measurements of a plastic sample.

Terahertz (THz) is an emerging technology particularly well suited for the non-destructive investigation of inner structures in polymers. To realize its full potential, THz imaging systems adapted to industrial constraints as well as more application studies in areas of interest are needed. In this work, we present a fast and flexible THz imaging system comprising hardware and software and demonstrate its capabilities for the investigation of defects in glass fiber-reinforced polymers (GFRPs), particularly for the detection of drilling-induced delaminations. Measurement data obtained by raster scanning of GFRP samples are gathered in 3D volumetric images. THz images of the drilled holes are then compared to reference images of the same holes obtained from X-ray computed tomography measurements. We show that THz imaging is capable of identifying not only artificial defects in the form of aluminum and Teflon inlays, but also real defects such as delaminations generated by drilling operations, and is suitable for non-destructive testing in industrial conditions.

In this paper, we consider the imaging problem of terahertz (THz) tomography, in particular as it appears in non-destructive testing. We derive a nonlinear mathematical model describing a full THz tomography experiment, and consider linear approximations connecting THz tomography with standard computerized tomography and the Radon transform. Based on the derived models we propose different reconstruction approaches for solving the THz tomography problem, which we then compare on experimental data obtained from THz measurements of a plastic sample.