Real-time quasi-3D tomographic reconstruction

Developments in acquisition technology and a growing need for time-resolved experiments pose great computational challenges in tomography. In addition, access to reconstructions in real time is a highly demanded feature but has so far been out of reach. We show that by exploiting the mathematical properties of filtered backprojection-type methods, having access to real-time reconstructions of arbitrarily oriented slices becomes feasible. Furthermore, we present RECAST3D, software for visualization and on-demand reconstruction of slices. A user of RECAST3D can interactively shift and rotate slices in a GUI, while the software updates the slice in real time. For certain use cases, the possibility to study arbitrarily oriented slices in real time directly from the measured data provides sufficient visual and quantitative insight. Two such applications are discussed in this article

BPF Algorithms for Multiple Source-Translation Computed Tomography Reconstruction

Micro-computed tomography (micro-CT) is a widely used state-of-the-art instrument employed to study the morphological structures of objects in various fields. Object-rotation is a classical scanning mode in micro-CT allowing data acquisition from different angles; however, its field-of-view (FOV) is primarily constrained by the size of the detector when aiming for high spatial resolution imaging. Recently, we introduced a novel scanning mode called multiple source translation CT (mSTCT), which effectively enlarges the FOV of the micro-CT system. Furthermore, we developed a virtual projection-based filtered backprojection (V-FBP) algorithm to address truncated projection, albeit with a trade-off in acquisition efficiency (high resolution reconstruction typically requires thousands of source samplings). In this paper, we present a new algorithm for mSTCT reconstruction, backprojection-filtration (BPF), which enables reconstructions of high-resolution images with a low source sampling ratio. Additionally, we found that implementing derivatives in BPF along different directions (source and detector) yields two distinct BPF algorithms (S-BPF and D-BPF), each with its own reconstruction performance characteristics. Through simulated and real experiments conducted in this paper, we demonstrate that achieving same high-resolution reconstructions, D-BPF can reduce source sampling by 75% compared with V-FBP. S-BPF shares similar characteristics with V-FBP, where the spatial resolution is primarily influenced by the source sampling.Comment: 22 pages, 12 figure

Sparse Matrix-Based HPC Tomography

Tomographic imaging has benefited from advances in X-ray sources, detectors and optics to enable novel observations in science, engineering and medicine. These advances have come with a dramatic increase of input data in the form of faster frame rates, larger fields of view or higher resolution, so high performance solutions are currently widely used for analysis. Tomographic instruments can vary significantly from one to another, including the hardware employed for reconstruction: from single CPU workstations to large scale hybrid CPU/GPU supercomputers. Flexibility on the software interfaces and reconstruction engines are also highly valued to allow for easy development and prototyping. This paper presents a novel software framework for tomographic analysis that tackles all aforementioned requirements. The proposed solution capitalizes on the increased performance of sparse matrix-vector multiplication and exploits multi-CPU and GPU reconstruction over MPI. The solution is implemented in Python and relies on CuPy for fast GPU operators and CUDA kernel integration, and on SciPy for CPU sparse matrix computation. As opposed to previous tomography solutions that are tailor-made for specific use cases or hardware, the proposed software is designed to provide flexible, portable and high-performance operators that can be used for continuous integration at different production environments, but also for prototyping new experimental settings or for algorithmic development. The experimental results demonstrate how our implementation can even outperform state-of-the-art software packages used at advanced X-ray sources worldwide

Erosion and dilation of edges in dimensional X-ray computed tomography images

Dimensional X-ray Computed Tomography (CT) is a rapidly expanding field of research due to the numerous advantages this technique offers over conventional measurement technologies, most notably, the ability to measure internal features of a component. Tactile and optical Coordinate Measurement Machines (CMM), currently used in the manufacturing production industry, record points on the external surface of a workpiece by measuring the contact point of a physical probe or the reflection of projected light. X-ray CT has the ability to capture full volumetric data, since X-rays are transmitted through the entire object, revealing features which are otherwise invisible. Over the past five years, interest in this field has grown in the UK, with an increasing number of organisations in industry and research having access to X-ray CT machines and the wide range of manufacturers, offering new systems specifically designed for dimensional metrology applications.Despite this, the complexity of data acquisition required for dimensional measurement using X-ray CT has made it difficult to estimate the measurement uncertainty. This has hindered the generation of standards and full-scale adoption of this technique in industry. Due to the nature of X-ray imaging, a number of non-linear influence factors exist which have the potential to cause dimensional measurement error. These influences must be better understood to reduce and ideally, compensate error.In this doctoral thesis, the effects of the influence factors associated with CT data acquisition are studied, specifically, beam hardening and a finite X-ray source size. The effects these have on the quality of X-ray CT data are well understood; typically degrading the achievable contrast and spatial resolution of the CT image. However, the effects on dimensional measurement are less well understood due to the complexity of their interactions before reconstruction of the final image. These influences are modelled in a simulated CT acquisition to quantify any systematic effects on determination of edges in the CT image. The results are then validated by experimentally replicating the simulation set-up.In this work, it is found that beam hardening and a finite source diameter can lead to systematic errors in the edge position within the CT image. Beam hardening generally leads to dilation of the edge; where the edge position moves in the direction of the surface vector. In contrast, a finite source diameter can lead to erosion of the edge; where the edge position moves in an opposing direction to the surface vector.</div

Theoretical and Experimental Evaluation of Spatial Resolution in a Variable Resolution X-Ray Computed Tomography Scanner

A variable resolution x-ray (VRX) computed tomography (CT) scanner can image objects of various sizes with greatly improved spatial resolution. The scanner employs an angulated discrete detector and achieves the resolution boost by matching the detector angulation to the scanner field of view (FOV) determined by the size of an object being imaged. A comprehensive evaluation of spatial resolution in an experimental version of the VRX CT scanner is presented in this dissertation. Two components of this resolution were evaluated – the pre-reconstruction spatial resolution, described by the detector presampling modulation transfer function (MTF), and the post-reconstruction spatial resolution, given by the scanner reconstruction MTF. The detector presampling MTF was modeled by the Monte Carlo simulation and measured by the moving-slit method. The modeled results showed the increase in the maximum cutoff frequency (in the detector plane) from 1.53 to 53.64 cycles per mm (cy/mm) as the scanner FOV decreased from 32 to 1 cm. The measured results supported the modeling, except for the small FOVs (below 8 cm), where the MTF could not be measured up to the cutoff frequency due to the focal-spot limitation. The scanner reconstruction MTF was measured by the special-phantom method. The measured results demonstrated the increase in the average cutoff frequency (in the object plane) from 2.44 to 4.13 cy/mm as the scanner FOV decreased from 16 to 8 cm. The MTF could not be measured at the FOVs other than 8 and 16 cm, due to the calibration-reconstruction inaccuracies and, again, the focal-spot limitation. Overall, the evaluation confirmed the potential value of the VRX CT scanner and produced results important for its further development

Geometrical Calibration and Filter Optimization for Cone-Beam Computed Tomography

This thesis will discuss the requirements of a software library for tomography and will derive a framework which can be used to realize various applications in cone-beam computed tomography (CBCT). The presented framework is self-contained and is realized using the MATLAB environment in combination with native low-level technologies (C/C++ and CUDA) to improve its computational performance, while providing accessibility and extendability through to use of a scripting language environment. On top of this framework, the realization of Katsevich’s algorithm on multicore hardware will be explained and the resulting implementation will be compared to the Feldkamp, Davis and Kress (FDK) algorithm. It will also be shown that this helical reconstruction method has the potential to reduce the measurement uncertainty. However, misalignment artifacts appear more severe in the helical reconstructions from real data than in the circular ones. Especially for helical CBCT (H-CBCT), this fact suggests that a precise calibration of the computed tomography (CT) system is inevitable. As a consequence, a self-calibration method will be designed that is able to estimate the misalignment parameters from the cone-beam projection data without the need of any additional measurements. The presented method employs a multi-resolution 2D-3D registration technique and a novel volume update scheme in combination with a stochastic reprojection strategy to achieve a reasonable runtime performance. The presented results will show that this method reaches sub-voxel accuracy and can compete with current state-of-the-art online- and offline-calibration approaches. Additionally, for the construction of filters in the area of limited-angle tomography a general scheme which uses the Approximate Inverse (AI) to compute an optimized set of 2D angle-dependent projection filters will be derived. Optimal sets of filters are then precomputed for two angular range setups and will be reused to perform various evaluations on multiple datasets with a filtered backprojection (FBP)-type method. This approach will be compared to the standard FDK algorithm and to the simultaneous iterative reconstruction technique (SIRT). The results of the study show that the introduced filter optimization produces results comparable to those of SIRT with respect to the reduction of reconstruction artifacts, whereby its runtime is comparable to that of the FDK algorithm

Advanced industrial X-ray computed tomography for defect detection and characterisation of composite structures

X-ray Computer Tomography (CT) is well suited to the inspection of Fibre-Reinforced-Plastic (FRP) composite materials. However, a range of limitations currently restrict its uptake. The aim of the present research was to develop advanced inspection procedures that overcome these limitations and increase the scope of composite structures that can be inspected by industrial cone beam CT. Region of Interest (ROI) CT inspection of FRP laminated panels was investigated and two data completion methods developed to overcome reconstruction errors caused by truncated projection data. These allow accurate, highly magnified regions to be reconstructed on objects that extend beyond the Field-of-View (FOV) of the detector. The first method extended the truncated projection data using a cosine signal tailing off to zero attenuation. This method removed the strong 'glowing' artefacts but an inherent error existed across the reconstructed ROI. This did not affect the defect detectability of the inspection but was viewed as problematic for applications requiring accurate density measurements. The second method used prior knowledge of the test object so that a model could be created to estimate the missing data. This technique removed errors associated with ROI reconstruction thus significantly improving the accuracy. Techniques for extending the FOV were developed and applied to the inspection of FRP wind turbine blades; over 1.5X larger than the conventional scanning FOV. Two data completion methods were developed requiring an asymmetrically positioned detector. The first was based on the cosine tailing technique and the second used fan beam ray redundancy properties to estimate the missing data. Both produced accurate reconstructions for the 'offset' projection data, demonstrating that it was possible to approximately double the FOV. The cosine tailing method was found to be the more reliable. A dual energy image CT technique was developed to extend the optimum dynamic range and improve defect detectability for multi-density objects. This was applied to FRP composite/Titanium lap joints showing improved detectability of both volumetric and planar defects within the low density FRP. The dual energy procedure was validated using statistical performance measures on a specially fabricated multi-density phantom. The results showed a significant improvement in the detail SNR when compared to conventional CT scans.EThOS - Electronic Theses Online ServiceTWI LtdThe Engineering and Physical Sciences Research Board (EPSRC)GBUnited Kingdo

Mathematical Methods in Tomography

This is the seventh Oberwolfach conference on the mathematics of tomography, the first one taking place in 1980. Tomography is the most popular of a series of medical and scientific imaging techniques that have been developed since the mid seventies of the last century