Metal Artifact Reduction in Spectral X-ray CT Using Spectral Deep Learning

Spectral X-ray computed tomography (SCT) is an emerging method for non-destructive imaging of the inner structure of materials. Compared with the conventional X-ray CT, this technique provides spectral photon energy resolution in a finite number of energy channels, adding a new dimension to the reconstructed volumes and images. While this mitigates energy-dependent distortions such as beam hardening, metal artifacts due to photon starvation effects are still present, especially for low-energy channels where the attenuation coefficients are higher. We present a correction method for metal artifact reduction in SCT that is based on spectral deep learning. The correction efficiently reduces streaking artifacts in all the energy channels measured. We show that the additional information in the energy domain provides relevance for restoring the quality of low-energy reconstruction affected by metal artifacts. The correction method is parameter free and only takes around 15 ms per energy channel, satisfying near-real time requirement of industrial scanners.

Using virtual reality for anatomical landmark annotation in geometric morphometrics

To study the shape of objects using geometric morphometrics, landmarks are oftentimes collected digitally from a 3D scanned model. The expert may annotate landmarks using software that visualizes the 3D model on a flat screen, and interaction is achieved with a mouse and a keyboard. However, landmark annotation of a 3D model on a 2D display is a tedious process and potentially introduces error due to the perception and interaction limitations of the flat interface. In addition, digital landmark placement can be more time-consuming than direct annotation on the physical object using a tactile digitizer arm. Since virtual reality (VR) is designed to more closely resemble the real world, we present a VR prototype for annotating landmarks on 3D models. We study the impact of VR on annotation performance by comparing our VR prototype to Stratovan Checkpoint, a commonly used commercial desktop software. We use an experimental setup, where four operators placed six landmarks on six grey seal (Halichoerus grypus) skulls in six trials for both systems. This enables us to investigate multiple sources of measurement error. We analyse both for the configuration and for single landmarks. Our analysis shows that annotation in VR is a promising alternative to desktop annotation. We find that annotation precision is comparable between the two systems, with VR being significantly more precise for one of the landmarks. We do not find evidence that annotation in VR is faster than on the desktop, but it is accurate.

Fundamental scattering quantities for the determination of reflectance and transmittance

The bidirectional reflectance distribution function (BRDF) and the bidirectional scattering - surface reflectance distribution function (BSSRDF), which relate radiance at the surface to irradiance and radiant flux, respectively, are regarded as the most fundamental scattering quantities used to determine the reflectance of objects. However, for materials where the optical radiation is transmitted under the surface, this radiance depends not only on irradiance and radiant flux, but also on the size of the irradiated area of the surface. This article provides insight into such dependence under the special condition in which the radiance is evaluated within the irradiated area and, consequently, is produced by both the insurface reflection and the subsurface scattering, in contrast to the situation in which the radiance is evaluated at non-irradiated areas and only subsurface scattering contributes. By explicitly considering both contributions, two other scattering quantities are defined: one that accounts exclusively for the insurface reflection and the other that accounts for subsurface scattering. In this regard, these quantities might be considered more fundamental than the BRDF and the BSSRDF, although they are coincident with these two functions apart from the above-mentioned special condition and for materials with negligible subsurface scattering. In this work, the relevance of the proposed scattering quantities is supported by experimental data, practical considerations are given for measuring them, and their relation to the bidirectional transmittance distribution function (BTDF) is discussed.

Non-invasive assessment of dairy products using spatially resolved diffuse reflectance spectroscopy

The quality of a dairy product is largely determined by its microstructure which also affects its optical properties. Consequently, an assessment of the optical properties during production may be part of a feedback system for ensuring the quality of the production process. This paper presents a novel camera-based measurement technique that enables robust quantification of a wide range of reduced scattering coefficients and absorption coefficients. Measurements are based on hyperspectral images of diffuse reflectance in the wavelength range of 470 to 1020 nm. The optical properties of commercially available milk and yogurt products with three different levels of fat content are measured. These constitute a relevant range of products at a dairy plant. The measured reduced scattering properties of the samples are presented and show a clear discrimination between levels of fat contents as well as fermentation. The presented measurement technique and method of analysis is thus suitable for a rapid, non-contact, and non-invasive inspection that can deduce physically interpretable properties.