Yoni De Witte

Three-dimensional analysis of high-resolution X-ray computed tomography data with Morpho+

Three-dimensional (3D) analysis is an essential tool to obtain quantitative results from 3D datasets. Considerable progress has been made in 3D imaging techniques, resulting in a growing need for more flexible, complete analysis packages containing advanced algorithms. At the Centre for X-ray Tomography of the Ghent University (UGCT), research is being done on the improvement of both hardware and software for high-resolution X-ray computed tomography (CT). UGCT collaborates with research groups from different disciplines, each having specific needs. To meet these requirements the analysis software package, Morpho+, was developed in-house. Morpho+ contains an extensive set of high-performance 3D operations to obtain object segmentation, separation, and parameterization (orientation, maximum opening, equivalent diameter, sphericity, connectivity, etc.), or to extract a 3D geometrical representation (surface mesh or skeleton) for further modeling. These algorithms have a relatively short processing time when analyzing large datasets. Additionally, Morpho+ is equipped with an interactive and intuitive user interface in which the results are visualized. The package allows scientists from various fields to obtain the necessary quantitative results when applying high-resolution X-ray CT as a research tool to the nondestructive investigation of the microstructure of materials.

Bronnikov-aided correction for x-ray computed tomography

When a very-low-absorbing sample is scanned at an x-ray computed tomography setup with a microfocus x-ray tube and a high-resolution detector, the obtained projection images contain not only absorption contrast but also phase contrast. While images without a phase signal can be reconstructed very well, such mixed phase and absorption images give rise to severe artifacts in the reconstructed slices. A method is described that applies a correction to these mixed projections to remove the phase signal. These corrected images can then be processed using a standard filtered backprojection algorithm to obtain reconstructions with only few or no phase artifacts. This new method, which we call the Bronnikov-aided correction (BAC), can be used in a broad variety of applications and without much additional effort. It is tested on a biological and a pharmaceutical sample, and results are evaluated and discussed by comparing them with those of conventional reconstruction methods.

Virtual histology by means of high-resolution X-ray CT

Micro‐CT is a non‐destructive technique for 3D tomographic investigation of an object. A 3D representation of the internal structure is calculated based on a series of X‐ray radiographs taken from different angles. The spatial resolution of current laboratory‐used micro‐CT systems has come down over the last years from a few tens of microns to a few microns. This opens the possibility to perform histological investigations in 3D on a virtual representation of a sample, referred to as virtual 3D histology. The advantage of micro‐CT based virtual histology is the immediate and automated 3D visualization of the sample without prior slicing, sample preparation like decalcification, photographing and aligning. This not only permits a drastic reduction in preparation time but also offers the possibility to easily investigate objects that are difficult to slice. This article presents results that were obtained on punch biopsies of horse skin, (dental) alveolus of ponies and chondro‐osseous samples from the tarsus of foals studied with the new high resolution micro‐CT set‐up (HRXCT) at the Ghent University (Belgium) (http://www.ugct.ugent.be). This state‐of‐the‐art set‐up provides a 1 micron resolution and is therefore ideally suited for a direct comparison with standard light microscopy–based histology.

High-resolution proxies for wood density variations in Terminalia superba.

BACKGROUND AND AIMS Density is a crucial variable in forest and wood science and is evaluated by a multitude of methods. Direct gravimetric methods are mostly destructive and time-consuming. Therefore, faster and semi- to non-destructive indirect methods have been developed. METHODS Profiles of wood density variations with a resolution of approx. 50 µm were derived from one-dimensional resistance drillings, two-dimensional neutron scans, and three-dimensional neutron and X-ray scans. All methods were applied on Terminalia superba Engl. & Diels, an African pioneer species which sometimes exhibits a brown heart (limba noir). KEY RESULTS The use of X-ray tomography combined with a reference material permitted direct estimates of wood density. These X-ray-derived densities overestimated gravimetrically determined densities non-significantly and showed high correlation (linear regression, R(2) = 0·995). When comparing X-ray densities with the attenuation coefficients of neutron scans and the amplitude of drilling resistance, a significant linear relation was found with the neutron attenuation coefficient (R(2) = 0·986) yet a weak relation with drilling resistance (R(2) = 0·243). When density patterns are compared, all three methods are capable of revealing the same trends. Differences are mainly due to the orientation of tree rings and the different characteristics of the indirect methods. CONCLUSIONS High-resolution X-ray computed tomography is a promising technique for research on wood cores and will be explored further on other temperate and tropical species. Further study on limba noir is necessary to reveal the causes of density variations and to determine how resistance drillings can be further refined.

Improved signal-to-noise ratio in laboratory-based phase contrast tomography.

In conventional X-ray microtomography (μCT), the three-dimensional (3D) distribution of the attenuation coefficient of X-rays is measured and reconstructed in a 3D volume. As spatial resolution increases, the refraction of X-rays becomes a significant phenomenon in the imaging process. Although this so-called phase contrast was initially a cumbersome feature in lab-based μCT, special phase retrieval algorithms were developed to exploit these effects. Clear advantages in terms of visualization and analysis can be seen when phase retrieval algorithms are applied, including an increased signal-to-noise ratio. In this work, this is demonstrated both on simulated and measured data.