Image reconstruction and correction methods in neutron and X-ray tomography

Neutron and X-ray tomography are imaging techniques for getting information about the interior of objects in a non-destructive way. They reconstruct cross-sections from projection images of the object being investigated. Due to the properties of the image acquisition system, the projection images are distorted by several artifacts, and these reduce the quality of the reconstruction. In order to eliminate these harmful effects the projection images should be corrected before reconstruction. Taking projections is usually an expensive and time consuming procedure. One of our main goals has been to try to minimize the number of projections - for example, by exploiting more a priori information. A possible way of reducing the number of projections is by the application of discrete tomographic methods. In this case a special class of objects can be reconstructed, consisting of only a few homogenous materials that can be characterized by known discrete absorption values. To this end we have implemented two reconstruction methods. One is able to reconstruct objects consisting of cylinders and spheres made of homogeneous materials only. The other method is a general one in the sense that it can be used for reconstructing any shape. Simulations on phantoms and physical measurements were carried out and the results are presented here

Statistical Image Reconstruction for High-Throughput Thermal Neutron Computed Tomography

Neutron Computed Tomography (CT) is an increasingly utilised non-destructive analysis tool in material science, palaeontology, and cultural heritage. With the development of new neutron imaging facilities (such as DINGO, ANSTO, Australia) new opportunities arise to maximise their performance through the implementation of statistically driven image reconstruction methods which have yet to see wide scale application in neutron transmission tomography. This work outlines the implementation of a convex algorithm statistical image reconstruction framework applicable to the geometry of most neutron tomography instruments with the aim of obtaining similar imaging quality to conventional ramp filtered back-projection via the inverse Radon transform, but using a lower number of measured projections to increase object throughput. Through comparison of the output of these two frameworks using a tomographic scan of a known 3 material cylindrical phantom obtain with the DINGO neutron radiography instrument (ANSTO, Australia), this work illustrates the advantages of statistical image reconstruction techniques over conventional filter back-projection. It was found that the statistical image reconstruction framework was capable of obtaining image estimates of similar quality with respect to filtered back-projection using only 12.5% the number of projections, potentially increasing object throughput at neutron imaging facilities such as DINGO eight-fold

Challenges in imaging and predictive modeling of rhizosphere processes

Background Plant-soil interaction is central to human food production and ecosystem function. Thus, it is essential to not only understand, but also to develop predictive mathematical models which can be used to assess how climate and soil management practices will affect these interactions. Scope In this paper we review the current developments in structural and chemical imaging of rhizosphere processes within the context of multiscale mathematical image based modeling. We outline areas that need more research and areas which would benefit from more detailed understanding. Conclusions We conclude that the combination of structural and chemical imaging with modeling is an incredibly powerful tool which is fundamental for understanding how plant roots interact with soil. We emphasize the need for more researchers to be attracted to this area that is so fertile for future discoveries. Finally, model building must go hand in hand with experiments. In particular, there is a real need to integrate rhizosphere structural and chemical imaging with modeling for better understanding of the rhizosphere processes leading to models which explicitly account for pore scale processes

Tomographic Study of Internal Erosion of Particle Flows in Porous Media

In particle-laden flows through porous media, porosity and permeability are significantly affected by the deposition and erosion of particles. Experiments show that the permeability evolution of a porous medium with respect to a particle suspension is not smooth, but rather exhibits significant jumps followed by longer periods of continuous permeability decrease. Their origin seems to be related to internal flow path reorganization by avalanches of deposited material due to erosion inside the porous medium. We apply neutron tomography to resolve the spatio-temporal evolution of the pore space during clogging and unclogging to prove the hypothesis of flow path reorganization behind the permeability jumps. This mechanistic understanding of clogging phenomena is relevant for a number of applications from oil production to filters or suffosion as the mechanisms behind sinkhole formation.Comment: 18 pages, 9 figure

Structural biology: a century-long journey into an unseen world

© Institute of Materials, Minerals and Mining 2015.When the first atomic structures of salt crystals were determined by the Braggs in 1912–1913, the analytical power of X-ray crystallography was immediately evident. Within a few decades the technique was being applied to the more complex molecules of chemistry and biology and is rightly regarded as the foundation stone of structural biology, a field that emerged in the 1950s when X-ray diffraction analysis revealed the atomic architecture of DNA and protein molecules. Since then the toolbox of structural biology has been augmented by other physical techniques, including nuclear magnetic resonance spectroscopy, electron microscopy, and solution scattering of X-rays and neutrons. Together these have transformed our understanding of the molecular basis of life. Here I review the major and most recent developments in structural biology that have brought us to the threshold of a landscape of astonishing molecular complexity

Crystalline phase discriminating neutron tomography using advanced reconstruction methods

Time-of-flight neutron imaging offers complementary attenuation contrast to X-ray computed tomography (CT), coupled with the ability to extract additional information from the variation in attenuation as a function of neutron energy (time of flight) at every point (voxel) in the image. In particular Bragg edge positions provide crystallographic information and therefore enable the identification of crystalline phases directly. Here we demonstrate Bragg edge tomography with high spatial and spectral resolution. We propose a new iterative tomographic reconstruction method with a tailored regularisation term to achieve high quality reconstruction from low-count data, where conventional filtered back-projection (FBP) fails. The regularisation acts in a separated mode for spatial and spectral dimensions and favours characteristic piece-wise constant and piece-wise smooth behaviour in the respective dimensions. The proposed method is compared against FBP and a state-of-the-art regulariser for multi-channel tomography on a multi-material phantom. The proposed new regulariser which accommodates specific image properties outperforms both conventional and state-of-the-art methods and therefore facilitates Bragg edge fitting at the voxel level. The proposed method requires significantly shorter exposure to retrieve features of interest. This in turn facilitates more efficient usage of expensive neutron beamline time and enables the full utilisation of state-of-the-art high resolution detectors

Deterministic simulation of thermal neutron radiography and tomography

In recent years, thermal neutron radiography and tomography have gained much attention as one of the nondestructive testing methods. However, the application of thermal neutron radiography and tomography hindered by their technical complexity, radiation shielding, and time-consuming data collection processes. Monte Carlo simulations have been developed in the past to improve the neutron imaging facility\u27s ability. In this present work, a new deterministic simulation approach has been proposed and demonstrated to simulate neutron radiographs numerically using a ray tracing algorithm. This approach has made the simulation of neutron radiographs much faster than by previously used stochastic methods (i.e Monte Carlo methods). The major problem with neutron radiography and tomography simulation is finding a suitable scatter model. In this paper, an analytic scatter model has been proposed that is validated by a Monte Carlo simulation. Two simulation geometries have been analyzed in this work. One is a highly scattering medium, another is medium scattering media. It has been shown that this algorithm works well in the medium scattering media. The scatter model has been verified using Monte Carlo method (MCNP5).There are some empirical parameters that have been determined using curve fitting methods using MATLAB. There are some disadvantages of using the scatter correction algorithm proposed in this work, but the advantages are far more rewarding. This method of simulation reduces the time of simulation in 5-10 seconds compared to several hours using Monte Carlo methods and can be used for rapid prototyping for neutron imaging facilities. Filtered back-projection with a ramp filter has been used for reconstruction --Abstract, page iii

Iterative CT reconstruction from few projections for the nondestructive post irradiation examination of nuclear fuel assemblies

The core components (e.g. fuel assemblies, spacer grids, control rods) of the nuclear reactors encounter harsh environment due to high temperature, physical stress, and a tremendous level of radiation. The integrity of these elements is crucial for safe operation of the nuclear power plants. The Post Irradiation Examination (PIE) can reveal information about the integrity of the elements during normal operations and off‐normal events. Computed tomography (CT) is a tool for evaluating the structural integrity of elements non-destructively. CT requires many projections to be acquired from different view angles after which a mathematical algorithm is adopted for reconstruction. Obtaining many projections is laborious and expensive in nuclear industries. Reconstructions from a small number of projections are explored to achieve faster and cost-efficient PIE. Classical reconstruction algorithms (e.g. filtered back projection) cannot offer stable reconstructions from few projections and create severe streaking artifacts. In this thesis, conventional algorithms are reviewed, and new algorithms are developed for reconstructions of the nuclear fuel assemblies using few projections. CT reconstruction from few projections falls into two categories: the sparse-view CT and the limited-angle CT or tomosynthesis. Iterative reconstruction algorithms are developed for both cases in the field of compressed sensing (CS). The performance of the algorithms is assessed using simulated projections and validated through real projections. The thesis also describes the systematic strategy towards establishing the conditions of reconstructions and finds the optimal imaging parameters for reconstructions of the fuel assemblies from few projections. --Abstract, page iii