Valeriy Titarenko

Region-of-interest tomography using filtered backprojection: assessing the practical limits

There are many cases where it is desirable to reconstruct at high resolution a small volume from a larger sample. Here we describe the outcomes of a reconstruction trial based on real samples aimed at delineating the practical limits to which a small region of interest can be viewed from a large sample. Our approach has been to artificially truncate the sinograms of whole sample scans to simulate region of interest tomography. A simple filtered back projection algorithm has been applied, with the sinograms extended laterally in a simple manner to make up for the truncated portions. The impact of the degree of truncation (from 0% down to 99%), the number of projections used, as well as the position of the region of interest, on the faithfulness of the reconstruction is evaluated for a range of sample types. We have assessed the nature of, and extent to which, artefacts are introduced and the degree to which simple strategies can minimize them to an acceptable level without the need for complex reconstruction algorithms, projection stitching strategies or very large detectors. It is found that for a wide range of objects the effect of truncation on feature detection is negligible and that excellent images can be reconstructed if the number of projections is calculated not on the basis of the number of pixels on the camera, but on the number of pixels that would be required to scan the whole sample at the chosen pixel resolution. This paper demonstrates that in many cases more sophisticated reconstruction strategies are not necessary.

Improved tomographic reconstructions using adaptive time dependent intensity normalization

The first processing step in synchrotron-based micro-tomography is the normalization of the projection images against the background, also referred to as a white field. Owing to time-dependent variations in illumination and defects in detection sensitivity, the white field is different from the projection background. In this case standard normalization methods introduce ring and wave artefacts into the resulting three-dimensional reconstruction. In this paper the authors propose a new adaptive technique accounting for these variations and allowing one to obtain cleaner normalized data and to suppress ring and wave artefacts. The background is modelled by the product of two time-dependent terms representing the illumination and detection stages. These terms are written as unknown functions, one scaled and shifted along a fixed direction (describing the illumination term) and one translated by an unknown two-dimensional vector (describing the detection term). The proposed method is applied to two sets (a stem Salix variegata and a zebrafish Danio rerio) acquired at the parallel beam of the micro-tomography station 2-BM at the Advanced Photon Source showing significant reductions in both ring and wave artefacts. In principle the method could be used to correct for time-dependent phenomena that affect other tomographic imaging geometries such as cone beam laboratory X-ray computed tomography.

Suppression of ring artefacts when tomographing anisotropically attenuating samples

There are many objects for which the attenuation varies significantly as they are rotated during computerized X-ray tomography, for example plate samples. This can lead to significant ring artefacts in the subsequent tomographic reconstructions. In this paper a new method is presented that can successfully suppress such ring artefacts and is applicable to both parallel and cone-beam geometries. Rapid correction is achieved via an analytical formula which involves only a matrix-vector multiplication, for which the matrix is known and depends on a regularization parameter. The efficacy of the method is demonstrated for a paleontological sample (calcified shark cartilage) and a carbon-carbon composite/Ti-SiC metal matrix composite test sample.

Regularization methods for inverse problems in X-ray tomography

Scintillators, optical systems and CCD cameras used to record projections also blur them. Therefore the recorded projections are smooth functions of spatial variables. This can be used to construct special methods to suppress ring artefacts. Several such algorithms based on ideas of the theory of inverse and ill-posed problems and using various forms of Tikhonov functional are proposed: a fast ring artefact suppression algorithm in a case of homogeneous specimens and its modified versions for anisotropically attenuated samples.

A ring artifact suppression algorithm based on a priori information

In this letter, ring artifacts in two-dimensional (2D) tomographic slices are considered. For a parallel beam geometry we propose an interactive algorithm, which removes the artifacts while preserving fine image details. The algorithm comprises two stages and is based on a priori information about the true attenuation coefficient in some areas of a 2D slice. Even in the absence of any a priori information the initial stage of the algorithm can already provide good ring artifact suppression.

Towards in-process x-ray CT for dimensional metrology

X-ray computed tomography (CT) offers significant potential as a metrological tool, given the wealth of internal and external data that can be captured, much of which is inaccessible to conventional optical and tactile coordinate measurement machines (CMM). Typical lab-based CT can take upwards of 30 min to produce a 3D model of an object, making it unsuitable for volume production inspection applications. Recently a new generation of real time tomography (RTT) x-ray CT has been developed for airport baggage inspections, utilising novel electronically switched x-ray sources instead of a rotating gantry. This enables bags to be scanned in a few seconds and 3D volume images produced in almost real time for qualitative assessment to identify potential threats. Such systems are able to scan objects as large as 600 mm in diameter at 500 mm s−1. The current voxel size of such a system is approximately 1 mm—much larger than lab-based CT, but with significantly faster scan times is an attractive prospect to explore. This paper will examine the potential of such systems for real time metrological inspection of additively manufactured parts. The measurement accuracy of the Rapiscan RTT110, an RTT airport baggage scanner, is evaluated by comparison to measurements from a metrologically confirmed CMM and those achieved by conventional lab-CT. It was found to produce an average absolute error of 0.18 mm that may already have some applications in the manufacturing line. While this is expectedly a greater error than lab-based CT, a number of adjustments are suggested that could improve resolution, making the technology viable for a broader range of in-line quality inspection applications, including cast and additively manufactured parts.

A priori information in a regularized sinogram-based method for removing ring artefacts in tomography

Ring artefacts in X-ray computerized tomography reconstructions are considered. The authors propose a ring artefact removal method based on a priori information regarding the sinogram including smoothness along the horizontal coordinate, symmetry of the first and the final rows and consideration of small perturbations during acquisition. The method does not require prior reconstruction of the original or corrected sinograms. Its numerical implementation is based on quadratic programming. Its efficacy is examined with regard to experimental data sets collected on graphite and bone.

A Graphical Processing Unit–Based Parallel Implementation of Multiplicative Algebraic Reconstruction Technique Algorithm for Limited View Tomography

This article proposes an efficient two-dimensional (2D) pixel-driven multiplicative algebraic reconstruction technique (PdMART) on a general purpose graphical processing unit (GPU), Nvidia graphics card GTX-275. It has been tested on numerical data and also on real data that have been obtained from the micro–computed tomography scanner installed at University of Manchester. We have used real data having 90 projections and 256 rays in each projection to test the algorithm. The real data has been obtained by scanning the graphite core object of size 30 mm × 30 mm. It has been found that GPU can help PdMART to generate the weight matrix for the 256 × 256 pixel grid within a second which is very fast compared to any sequential machine. Experimental results reveal that PdMART on GPU is computationally inexpensive. Preliminary results also indicate much better performance (as compared to popular Fourier methods) for cases of limited-view projection data as is the case for the upcoming laminographic tomography machines.

1-D Filter for Ring Artifact Suppression

Reconstruction algorithms in X-ray tomography provide a user with a set of images. For many scientific problems, these images should be segmented. Ring artifacts are the most noticeable artifacts that do not allow a scientist to achieve acceptable segmentation especially in case of noisy input data. Several ring artifact suppression methods based on theory of ill-posed problems exist. In this letter, the basic ring artifact suppression algorithm is rewritten as a 1-D filter, so it does not require separate data processing and can be combined with standard filtering used in filtered backprojection (FBP) algorithms.

Towards a portable open-source tomography toolbox: Containerizing tomography software with docker

We report on an ongoing project to create a portable tomography toolbox to enable the processing of user data on various computing platforms. Our goal is to create a collection of open source software applications in a single integrated package that is cross-platform, to facilitate analysis and interpretation of tomographic data emerging from the Brookhaven National Synchrotron Light Source (NSLS) II and Center for Functional Nanomaterials (CFN) facilities as well as other locations. The emerging container technology Docker makes it possible to integrate independent software packages in a single toolbox and allows us to abstract away the library and platform dependencies from the user’s point of view and develop a portable toolbox. To demonstrate, we Dockerized TomoPy and tomo display, two popular tomographic image processing software packages, and used them to analyze the images obtained at the NSLS X2B beam line. We also report some advances in the artifact-removal algorithms which will be an integral p...