Ordered subsets convex algorithm for 3D terahertz transmission tomography

Terahertz time-domain spectro-imaging and hyperspectral imagery to investigate a historical Longwy glazed ceramic

In this paper, we present the potential of Terahertz Time-Domain Imaging (THz-TDI) as a tool to perform non-invasive 3D analysis of an ancient enamel plate manufactured by Longwy Company in France. The THz data collected in the reflection mode were processed using noise filtering procedures and an advanced imaging approach. The results validate the capability to identify glaze layers and the thickness of ceramic materials. To characterize the nature of the pigments, we also use with X-ray images, visible near-infrared hyperspectral imaging spectroscopy, and p-XRF (portable X-ray fluorescence) to qualitatively and quantitively identify the materials used. The obtained information enables a better understanding of the decoration chromogens nature and, thus, to determine the color palette of the artists who produced such decorative object. We also establish the efficiency of a focus, Z-tracker, which enables to perform THz imaging on non-flat samples and to attenuate artifacts obtained with a short focus lens. Then, 3D images are extracted and generated, providing a real vision. We also report the evaluation of the internal damage state through the detection of fractures.

Measurement of the three-dimensional distribution of uniaxial stress by terahertz time domain spectroscopy

This paper presents a method to measure the three-dimensional distribution of uniaxial stress based on Terahertz Time Domain Spectroscopy (THz-TDS). The measurement principle was first established, which combines the computed tomography (CT) method and the photo-elastic effects. A classic filtered back-projection algorithm is adopted to calculate the three-dimensional stress fields from THz-TDS scanning images. Then, in verification experiment, the uniaxial stress distribution in the compressed cylinder and the stretched screw is obtained based on the measurement principle. Finally, the reliability of the proposed method has been verified by comparing the experiment results with the finite element simulation. A reasonable agreement is obtained.

Terahertz spatio-temporal deep learning computed tomography

Terahertz computed tomography (THz CT) has drawn significant attention because of its unique capability to bring multi-dimensional object information from invisible to visible. However, current physics-model-based THz CT modalities present low data use efficiency on time-resolved THz signals and low model fusion extensibility, limiting their application fields' practical use. In this paper, we propose a supervised THz deep learning computed tomography (THz DL-CT) framework based on time-domain information. THz DL-CT restores superior THz tomographic images of 3D objects by extracting features from spatio-temporal THz signals without any prior material information. Compared with conventional and machine learning based methods, THz DL-CT delivers at least 50.2%, and 52.6% superior in root mean square error (RMSE) and structural similarity index (SSIM), respectively. Additionally, we have experimentally demonstrated that the pretrained THz DL-CT model can generalize to reconstruct multi-material systems with no prerequisite information. THz CT through the DL data fusion approach provides a new pathway for non-invasive functional imaging in object investigation.

3D image reconstruction of terahertz computed tomography at sparse angles by total variation minimization

Continuous-wave terahertz computed tomography (THz-CT) is an important three-dimensional imaging method for probing the profile and inner properties of a sample's structure. We applied the total variation (TV) minimization iterative algorithm to squeeze 75% data acquisition time of THz-CT without the loss of reconstruction fidelity. The imaging system is built based on a 278.6 GHz avalanche diode source. A zero-order Bessel beam is generated by an axicon, for which the intensity profile remains essentially propagation invariant within the non-diffracting zone. The effectiveness of the proposed method is verified by using three optically opaque objects. The reconstruction results show that the TV-minimization algorithm can effectively suppress noise, artefacts, and shape distortion created in sparse angle reconstruction.

A Versatile Illumination System for Real-Time Terahertz Imaging

Terahertz technologies are attracting strong interest from high-end industrial fields, and particularly for non-destructive-testing purposes. Currently lacking compactness, integrability as well as adaptability for those implementations, the development and commercialisation of more efficient sources and detectors progressively ensure the transition toward applicative implementations, especially for real-time full-field imaging. In this work, a flexible illumination system, based on fast beam steering has been developed and characterized. Its primary goal is to suppress interferences induced by the coherence length of certain terahertz sources, spoiling terahertz images. The second goal is to ensure an enhanced signal-to-noise ratio on the detector side by the full use and optimized distribution of the available power. This system provides a homogeneous and adjustable illumination through a simplified setup to guarantee optimum real-time imaging capabilities, tailored to the sample under inspection. Working toward industrial implementations, different illumination process are conveniently assessed as a result of the versatility of this method.

Liquid index matching for 2D and 3D terahertz imaging

Two-dimensional (2D) terahertz imaging and 3D visualization suffer from severe artifacts since an important part of the terahertz beam is reflected, diffracted, and refracted at each interface. These phenomena are due to refractive index mismatch and reflection in the case of non-orthogonal incidence. This paper proposes an experimental procedure that reduces these deleterious optical refraction effects for a cylinder and a prism made with polyethylene material. We inserted these samples in a low absorption liquid medium to match the sample index. We then replaced the surrounding air with a liquid with an optimized refractive index, with respect to the samples being studied. Using this approach we could more accurately recover the original sample shape by time-of-flight tomography.

Terahertz imaging and tomography as efficient instruments for testing polymer additive manufacturing objects

Additive manufacturing (AM) technology is not only used to make 3D objects but also for rapid prototyping. In industry and laboratories, quality controls for these objects are necessary though difficult to implement compared to classical methods of fabrication because the layer-by-layer printing allows for very complex object manufacturing that is unachievable with standard tools. Furthermore, AM can induce unknown or unexpected defects. Consequently, we demonstrate terahertz (THz) imaging as an innovative method for 2D inspection of polymer materials. Moreover, THz tomography may be considered as an alternative to x-ray tomography and cheaper 3D imaging for routine control. This paper proposes an experimental study of 3D polymer objects obtained by additive manufacturing techniques. This approach allows us to characterize defects and to control dimensions by volumetric measurements on 3D data reconstructed by tomography.

Quantitative Analysis of Hexahydro-1,3,5-trinitro-1,3,5, Triazine/Pentaerythritol Tetranitrate (RDX-PETN) Mixtures by Terahertz Time Domain Spectroscopy

Absorption spectra of explosives such as hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX), pentaerythritol tetranitrate (PETN), and mixtures of both were measured by terahertz time domain spectroscopy (THz-TDS). Chemometrics was applied to quantitative analysis of terahertz absorbance spectra obtained in transmission mode to predict the relative amounts of RDX and PETN in samples containing pure components or their mixtures. This analysis was challenging because significant spectral overlap prevented identification of each product fingerprint. Partial least squares (PLS) regression models were thus applied to the terahertz spectra. A comparison between the so-called PLS1 and PLS2 algorithms was performed to predict the PETN concentrations in mixture samples. PLS2 demonstrated better predictive ability than PLS1 with RMSE value lower than 3.5 mg for 400 mg total weight pellets. Moreover, the influence of the highly overlapping spectral frequency band was investigated by reducing the original 0.2-3 THz (6-100 cm(-1)) spectral band to 1.8-3 THz (60-100 cm(-1)). The predictive ability was quite similar in both cases, highlighting the excellent ability of chemometrics to perform quantitative analysis when applied to THz-TDS data, even in the case of highly overlapping spectra.

Low-frequency noise effect on terahertz tomography using thermal detectors

In this paper, the impact of low-frequency noise on terahertz-computed tomography (THz-CT) is analyzed for several measurement configurations and pyroelectric detectors. We acquire real noise data from a continuous millimeter-wave tomographic scanner in order to figure out its impact on reconstructed images. Second, noise characteristics are quantified according to two distinct acquisition methods by (i) extrapolating from experimental acquisitions a sinogram for different noise backgrounds and (ii) reconstructing the corresponding spatial distributions in a slice using a CT reconstruction algorithm. Then we describe the low-frequency noise fingerprint and its influence on reconstructed images. Thanks to the observations, we demonstrate that some experimental choices can dramatically affect the 3D rendering of reconstructions. Thus, we propose some experimental methodologies optimizing the resulting quality and accuracy of the 3D reconstructions, with respect to the low-frequency noise characteristics observed during acquisitions.