A software system has been developed for high-performance Computed Tomography (CT) reconstruction, simulation
and other X-ray image processing tasks utilizing remote computer clusters optionally equipped with multiple Graphics
Processing Units (GPUs). The system has a streamlined Graphical User Interface for interaction with the cluster. Apart
from extensive functionality related to X-ray CT in plane-wave and cone-beam forms, the software includes multiple
functions for X-ray phase retrieval and simulation of phase-contrast imaging (propagation-based, analyzer crystal based
and Talbot interferometry). Other features include several methods for image deconvolution, simulation of various
phase-contrast microscopy modes (Zernike, Schlieren, Nomarski, dark-field, interferometry, etc.) and a large number of
conventional image processing operations (such as FFT, algebraic and geometrical transformations, pixel value
manipulations, simulated image noise, various filters, etc.). The architectural design of the system is described, as well as
the two-level parallelization of the most computationally-intensive modules utilizing both the multiple CPU cores and
multiple GPUs available in a local PC or a remote computer cluster. Finally, some results about the current system
performance are presented. This system can potentially serve as a basis for a flexible toolbox for X-ray image analysis
and simulation, that can efficiently utilize modern multi-processor hardware for advanced scientific computations.
We have constructed a helical trajectory X-ray micro-CT system which enables high-resolution tomography
within practical acquisition times. In the quest for ever-increasing resolution, lab-based X-ray micro-CT systems
are limited by the spot size of the X-ray source. Unfortunately, decreasing the spot size reduces the X-ray flux,
and therefore the signal-to-noise ratio (SNR). The reduced source flux can be offset by moving the detector closer
to the source, thereby capturing a larger solid angle of the X-ray beam. We employ a helical scanning trajectory,
accompanied by an exact reconstruction method to avoid the artifacts resulting from the use of large cone-angles
with circular trajectories. In this paper, we present some challenges which arise when adopting this approach in
a high-resolution cone-beam micro-CT system.
We present a description of our departments work flow that utilises X-ray micro-tomography in the observation and
prediction of physical properties of porous rock. These properties include fluid flow, dissolution/deposition, fracture
mapping, and mechanical processes, as well as measurement of three-dimensional (3D) morphological attributes such as
pore/grain size and shape distributions, and pore/grain connectivity. To support all these areas there is a need for well
integrated and parallel research programs in hardware development, structural description and physical property
modelling. Since we have the ability to validate simulation with physical measurement, (and vice versa), an important
part of the integration of all these techniques is calibration at every stage of the work flow. For example, we can use
high-resolution scanning electron microscopy (SEM) images to verify or improve our sophisticated segmentation
algorithm based on image grey-levels and gradients. The SEM can also be used to obtain sub-resolution porosity
information estimated from tomographic grey-levels and texture. Comparing experimental and simulated mercury
intrusion porosimetry can quantify the effective resolution of tomograms and the accuracy of segmentation. The
foundation of our calibration techniques is a robust and highly optimised 3D to 3D image-based registration method.
This enables us to compare the tomograms of successively disturbed (e.g., dissolved, fractured, cleaned, ...) specimens
with an original undisturbed state. A two-dimensional (2D) to 3D version of this algorithm allows us to register
microscope images (both SEM and quantitative electron microscopy) of prepared 2D sections of each specimen. This
can assist in giving a multimodal assessment of the specimen.
We present a simple, robust, and versatile solution to the problem of blurred tomographic images as a result of
imperfect geometric hardware alignment. The necessary precision for the alignment between the various components
of a tomographic instrument is in many cases technologically difficult to implement, or requires impractical
stability. Misaligned projection sets are not self-consistent and give blurred tomographic reconstructions. We
have developed an off-line software method that utilises a geometric model to parameterise the alignment, and
an algorithm for determining the alignment parameter set that gives the sharpest tomogram. It is an adaptation
of passive auto-focus methods that have been used to obtain sharp images in optical instruments for decades.
To minimise computation time, the auto-focus strategy is a multi-scale iterative technique implemented on a
selection of 2D cross-sections of the tomogram. For each cross-section, the sharpness is evaluated while scanning
over various combinations of alignment parameters. The parameter set that maximises sharpness is used to reconstruct
the 3D tomogram. To apply the corrections, the projection data are re-mapped, or the reconstruction
algorithm is modified. The entire alignment process takes less time than that of a full-scale 3D reconstruction. It
can in principle be applied to any cone or parallel beam CT with circular, helical, or more general trajectories. It
can also be applied retrospectively to archived projection data without any additional information. This concept
is fully tested and implemented for routine use in the ANU micro-CT reconstruction software suite and has made
the entire reconstruction pipeline robust and autonomous.
A microcomputed tomography (μCT) facility and computational infrastructure developed at the Department of Applied Mathematics at the Australian National University is described. The current experimental facility is capable of acquiring 3D images made up of 20003 voxels on porous specimens up to 60 mm diameter with resolutions down to 2 μm. This allows the three-dimensional (3D) pore-space of porous specimens to be imaged over several orders of magnitude. The computational infrastructure includes the establishment of optimised and distributed memory parallel algorithms for image reconstruction, novel phase identification, 3D visualisation, structural characterisation and prediction of mechanical and transport properties directly from digitised tomographic images. To date over 300 porous specimens exhibiting a wide variety of microstructure have been imaged and analysed. In this paper, analysis of a small set of porous rock specimens with structure ranging from unconsolidated sands to complex carbonates are illustrated. Computations made directly on the digitised tomographic images have been compared to laboratory measurements. The results are in excellent agreement. Additionally, local flow, diffusive and mechanical properties can be numerically derived from solutions of the relevant physical equations on the complex geometries; an experimentally intractable problem. Structural analysis of data sets includes grain and pore partitioning of the images. Local granular partitioning yields over 70,000 grains from a single image. Conventional grain size, shape and connectivity parameters are derived. The 3D organisation of grains can help in correlating grain size, shape and orientation to resultant physical properties. Pore network models generated from 3D images yield over 100000 pores and 200000 throats; comparing the pore structure for the different specimens illustrates the varied topology and geometry observed in porous rocks. This development foreshadows a new numerical laboratory approach to the study of complex porous materials.
A fully integrated X-ray tomography facility with the ability to generate tomograms with 20483 voxels at 2 micron spatial resolution was built to satisfy the requirements of a virtual materials testing laboratory. The instrument comprises of a continuously pumped micro-focus X-ray gun, a milli-degree rotation stage and a high resolution and large field X-ray camera, configured in a cone beam geometry with a circular trajectory. The purpose of this facility is to routinely analyse and investigate real world biological, geological and synthetic materials at a scale in which the traditional domains of physics, chemistry, biology and geology merge. During the first 2 years of operation, approximately 4 Terabytes of data have been collected, processed and analysed, both as static and in some cases as composite dynamic data sets. This incorporates over 300 tomograms with 10243 voxels and 50 tomograms with 20483 voxels for a wide range of research fields. Specimens analysed include sedimentary rocks, soils, bone, soft tissue, ceramics, fibre-reinforced composites, foams, wood, paper, fossils, sphere packs, bio-morphs and small animals. In this paper, the flexibility of the facility is highlighted with some