2024-03-28T22:40:41Z
https://zenodo.org/oai2d
oai:zenodo.org:61894
2020-01-20T17:40:54Z
user-mxif
user-ccpi
openaire
O'Sullivan, James
Else, Kathryn
Behnsen, Julia
Starborg, Tobias
Cruickshank, Sheena
Macdonald, Andrew
Withers, Philip
2016-09-07
<p>Trichuriasis is a tropical disease that affects an estimated 500 million people worldwide, especially children in tropical regions. It is caused by a parasitic nematode, Trichuris trichiura (whipworm). Current drugs lack efficacy, and there is no vaccine. Adult worms live partially buried in the mucosal epithelium of the intestine of the host, which makes them hard to study by traditional microscopy methods. As a consequence, little is known about how they feed, develop, and avoid the immune response of the host.</p>
<p>Micro X-ray CT of largely intact sections of intestine allows studying the intimate relationship between the parasite and host epithelium whilst avoiding the more damaging cutting of samples needed for 2D microscopy methods. In this contribution, we present data from adult Trichuris muris parasites found within infected mice. A scanning electron microscopy staining protocol was used for fixing and staining 5 mm sections of gut and caecum of the mice. Osmium tetroxide, used as a staining agent, was effective at producing x-ray absorption contrast in adult worms and their internal morphology, including the bacillary band, stichosome and oesophagus.</p>
<p>Novel observations about the positioning of the parasites were gained during this work. The heads of four out of six adult worms analysed were found to be orientated down the Crypts of Lieberkühn towards the basal lamina. Stichosome exposure to the lumen has relevance to novel drug development as epithelial penetrance of current anthelminthic drugs is poor. We measured the length of the exposed stichosome and the number of breaks in the epithelial layer covering the tunnel that the worm creates. Even though variance between worms is high, a part of the stichosome was always found to be exposed to the lumen.</p>
<p>We show that X-ray tomography is an effective approach to gain spatial and morphological information about Trichuris muris. In addition our data reveal T. muris in the mouse to be a useful model system with which to optimise imaging methodologies for the analyses of soft tissues in health and in disease.</p>
https://doi.org/10.5281/zenodo.61894
oai:zenodo.org:61894
Zenodo
https://zenodo.org/communities/ccpi
https://zenodo.org/communities/mxif
https://doi.org/
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
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trichuris muris
trichiuriasis
whipworm
parasite
nematode
gut
intestine
micro-CT
CT
microcomputed tomography
Visualising the parasitic whipworm Trichuris muris using X-ray micro-computed tomography
info:eu-repo/semantics/conferencePoster
oai:zenodo.org:61797
2020-01-20T17:03:21Z
user-ipuom
user-mxif
user-ccpi
openaire
Lionheart,William
Desai,Naeem
Schmidt, Søren
Withers, Philip
2016-09-08
<p>We outline rich tomography methods concentrating on tensor tomography of strain using gamma rays and monochromatic ex-rays, and neutron spin tomography for magnetic fields</p>
https://doi.org/10.5281/zenodo.61797
oai:zenodo.org:61797
Zenodo
https://zenodo.org/communities/ipuom
https://zenodo.org/communities/ccpi
https://zenodo.org/communities/mxif
https://doi.org/
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
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ToScA, Tomography for Sceintific Advancement, Bath,UK, 6-7 September 2016
strain tomography
rich tomography
non-abelian tomography
neutron spin tomography
x-ray diffraction tomography
Rich and Nonabelian Tomography: strain and magnetic fields
info:eu-repo/semantics/lecture
oai:zenodo.org:33881
2020-01-25T07:25:54Z
user-ipuom
user-mxif
user-ccpi
software
Sophia Bethany Coban
2015-11-17
<p>This is the second release of the codes, which are written for the SophiaBeads Datasets Project.</p>
<p>These codes are essential to work with the SophiaBeads Datasets. As before, the release contains scripts for loading the datasets, pre-reconstruction steps, and a reconstruction algorithm (cgls_XTek) as a template.</p>
<p>Improvements: This release is more adapted to different operating systems, and also includes a new function called <strong>scrollView</strong>. The function allows the users to view the reconstructed volumes along a chosen dimension within the same window. Type <em>help scrollView</em> in the command window to find out more.</p>
<p>More information can be found on the GitHub project page.</p>
https://doi.org/10.5281/zenodo.33881
oai:zenodo.org:33881
Zenodo
https://github.com/Sophilyplum/sophiabeads-datasets/tree/v2.0
https://zenodo.org/communities/ipuom
https://zenodo.org/communities/ccpi
https://zenodo.org/communities/mxif
https://doi.org/10.5281/zenodo.593371
info:eu-repo/semantics/openAccess
Other (Open)
SophiaBeads Datasets Project Codes
info:eu-repo/semantics/other
oai:zenodo.org:290117
2020-01-24T19:26:07Z
user-ipuom
user-mxif
user-ccpi
openaire_data
Jørgensen, J. S.
Coban, S. B.
Lionheart, W. R. B.
McDonald, S. A.
Withers, P. J.
2017-01-30
<p>The presented data set, inspired by the SophiaBeads Dataset Project for X-ray Computed Tomography, is collected for studies involving sparsity-regularised reconstruction. The aim is to provide tomographic data for various samples where the sparsity in the image varies.</p>
<p> </p>
<p>This dataset is made available as part of the publication</p>
<blockquote>
<p>"<strong><em>SparseBeads Data: Benchmarking Sparsity-Regularized Computed Tomography</em></strong>", Jakob S Jørgensen <em>et al,</em> 2017. <em>Meas. Sci. Technol.</em> <strong>28</strong> 124005.</p>
</blockquote>
<p>Direct link: https://doi.org/10.1088/1361-6501/aa8c29.</p>
<p>This manuscript is published as part of Special Feature on Advanced X-ray Tomography (open access). We refer the users to this publication for an extensive detail in the experimental planning and data acquisition.</p>
<p> </p>
<p>Each zipped data folder includes</p>
<ul>
<li>
<p>The meta data for data acquisition and geometry parameters of the scan (<strong>.xtekct</strong> and <strong>.ctprofile.xml)</strong>.</p>
</li>
<li>
<p>A sinogram of the central slice (CentreSlice > Sinograms > <strong>.tif</strong>) along with meta data for the 2D slice (<strong>.xtek2dct</strong> and <strong>.ct2dprofile.xml</strong>),</p>
</li>
<li>
<p>List of projection angles (<strong>.ang</strong>)</p>
</li>
<li>
<p>and a 2D FDK reconstruction using the CTPro reconstruction suite (RECON2D > .<strong>vol</strong>) with volume visualisation parameters (<strong>.vgi</strong>), added as a reference.</p>
</li>
</ul>
<p> </p>
<p>We also include an extra script for those that wish to use the SophiaBeads Dataset Project Codes, which essentially replaces the main script provided, <strong>sophiaBeads.m</strong> (visit https://zenodo.org/record/16539). Please note that <strong>sparseBeads.m</strong> script will have to be placed in the same folder as the project codes. The latest version of this script can be found here: https://github.com/jakobsj/SparseBeads_code</p>
<p> </p>
<p>For more information, please contact</p>
<ul>
<li>jakj [at] dtu.dk</li>
<li>jakob.jorgensen [at] manchester.ac.uk</li>
</ul>
JSJ was supported by the project ``High-Definition Tomography'' funded by Advanced Grant No. 291405 from the European Research Council. JSJ is grateful to the Schools of Mathematics and Materials, University of Manchester for hosting him during the work. SBC was supported by the School of Mathematics, University of Manchester, EPSRC CCPi (EP/J010456/1), and BP through the BP International Centre for Advanced Materials (BP-ICAM). WRBL acknowledges support from a Royal Society Wolfson Research Merit Award. SAM is grateful for funding through ZEISS. Authors acknowledge use of the Henry Moseley X-ray Imaging Facility at the University of Manchester, funded from the EPSRC under EP/F007906/1, EP/F028431/1, EP/I02249X/1 and EP/M022498/1 as well as Advanced Grant No. 695638 ``Correlative Tomography'' from the European Research Council.
https://doi.org/10.5281/zenodo.290117
oai:zenodo.org:290117
Zenodo
https://github.com/jakobsj/SparseBeads_code
https://zenodo.org/communities/ipuom
https://zenodo.org/communities/ccpi
https://zenodo.org/communities/mxif
https://doi.org/
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Creative Commons Attribution 4.0 International
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computed tomography
sparse image reconstruction
sparsity
SparseBeads Dataset
info:eu-repo/semantics/other
oai:zenodo.org:4352944
2022-01-06T21:48:21Z
user-mxif
user-ccpi
openaire_data
Ryan Warr
Jakob Sauer Jørgensen
Evangelos Papoutsellis
Evelina Ametova
Stephan Handschuh
Robert Cernik
Philip J. Withers
2020-12-18
<p><strong>General Data description:</strong></p>
<p>This is a hyperspectral (energy-resolved) X-ray CT projection dataset of a lizard head sample, stained with an iodine contrast agent. It was acquired in a custom-built, laboratory micro-CT scanner with an energy-sensitive HEXITEC detector in the Henry Moseley X-ray Imaging Facility at The University of Manchester.</p>
<p>The following data contains all the files necessary for reconstruction, after a hyperspectral scan was taken of a single, iodine-stained lizard head sample. The iodine contrast agent provided a spectral marker, measured by an energy-sensitive detector, which may be used for spatial mapping and segmentation of stained soft tissue regions.</p>
<p><strong>File descriptions:</strong></p>
<p>Contained are three MATLAB (.mat) data files, as well as a single text (.txt) file.</p>
<p>Lizard_head_scan_parameters.txt provides the full sample and detector geometry of the scan acquisition.</p>
<p>lizard_head_sinogram_full.mat contains the full 4D sinogram constructed following flatfield normalisation of the raw projection data. The 4D array contains the total number of energy channels acquired during scanning, followed by vertical and horizontal pixel number, and finally total projections angles acquired. The data provided is prior to application of any post-processing filters.</p>
<p>Energy_axis.mat provides a direct conversion between the energy channels, and the energies (in keV) that they correspond to, following a calibration procedure prior to scanning.</p>
<p>FF.mat contains the 4D flatfield data acquired when no sample was present. This data was used to normalise the projection datasets, as the sinogram was constructed.</p>
https://doi.org/10.5281/zenodo.4352944
oai:zenodo.org:4352944
eng
Zenodo
https://zenodo.org/communities/ccpi
https://zenodo.org/communities/mxif
https://doi.org/10.5281/zenodo.4352943
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
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Hyperspectral
Bioimaging
X-ray CT
Hyperspectral X-ray CT dataset of a single, iodine-stained lizard head sample
info:eu-repo/semantics/other
oai:zenodo.org:4737468
2022-01-06T21:48:22Z
user-mxif
user-ccpi
openaire_data
Ryan Warr
Jakob Sauer Jørgensen
Evangelos Papoutsellis
Evelina Ametova
Stephan Handschuh
Robert Cernik
Philip J. Withers
2021-05-04
<p><strong>General Data description:</strong></p>
<p>This is a hyperspectral (energy-resolved) X-ray CT projection dataset of a lizard head sample, stained with an iodine contrast agent. It was acquired in a custom-built, laboratory micro-CT scanner with an energy-sensitive HEXITEC detector in the Henry Moseley X-ray Imaging Facility at The University of Manchester.</p>
<p>The following data contains all the files necessary for reconstruction, after a hyperspectral scan was taken of a single, iodine-stained lizard head sample. The iodine contrast agent provided a spectral marker, measured by an energy-sensitive detector, which may be used for spatial mapping and segmentation of stained soft tissue regions.</p>
<p><strong>File descriptions:</strong></p>
<p>Contained are three MATLAB (.mat) data files, as well as a single text (.txt) file.</p>
<p>Lizard_head_scan_parameters.txt provides the full sample and detector geometry of the scan acquisition.</p>
<p>lizard_head_sinogram_full.mat contains the full 4D sinogram constructed following flatfield normalisation of the raw projection data. The 4D array contains the total number of energy channels acquired during scanning, followed by vertical and horizontal pixel number, and finally total projections angles acquired. The data provided is prior to application of any post-processing filters. The full set of 200 energy channels are included.</p>
<p>Energy_axis.mat provides a direct conversion between the energy channels, and the energies (in keV) that they correspond to, following a calibration procedure prior to scanning.</p>
<p>FF.mat contains the 4D flatfield data acquired when no sample was present. This data was used to normalise the projection datasets, as the sinogram was constructed. The full set of 200 energy channels are included.</p>
https://doi.org/10.5281/zenodo.4737468
oai:zenodo.org:4737468
eng
Zenodo
https://zenodo.org/communities/ccpi
https://zenodo.org/communities/mxif
https://doi.org/10.5281/zenodo.4352943
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
Hyperspectral
Bioimaging
X-ray CT
Hyperspectral X-ray CT dataset of a single, iodine-stained lizard head sample
info:eu-repo/semantics/other
oai:zenodo.org:18295
2020-01-20T17:00:14Z
user-ipuom
user-mxif
openaire
Coban, S.B.
Withers, P.J.
Lionheart, W.R.B.
McDonald, S.A.
2015-06-01
<p>A driving force for the development of new reconstruction algorithms is to achieve better quality images using less information (lower dose, fewer projections, in less time), but under what circumstances do iterative methods become worth the effort? In this paper we propose a framework that enables the performance of reconstruction algorithms to be mapped. Such a framework allows fair comparisons to be made, providing insights into experimental acquisition strategies and methods of quantifying the quality of reconstructions, and identifying the sweet spot for different algorithms. </p>
https://doi.org/10.5281/zenodo.18295
oai:zenodo.org:18295
Zenodo
https://doi.org/10.5281/zenodo.16474
http://eprints.ma.man.ac.uk/2290/
https://zenodo.org/communities/ipuom
https://zenodo.org/communities/mxif
https://doi.org/
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
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Fully3D 2015, The 13th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, Newport, Rhode Island, USA, May 31 to June 4, 2015
x-ray
computed tomography
iterative reconstruction methods
comparison of algorithms
sophiabeads-dataset
quantification
When do the iterative reconstruction methods become worth the effort?
info:eu-repo/semantics/lecture
oai:zenodo.org:1478688
2020-01-21T07:22:58Z
user-mxif
openaire_data
Ying Wang
Lars P. Mikkelsen
Grzegorz Pyka
Philip J. Withers
2018-11-21
<p>The X-ray CT data here is published with the paper - </p>
<p>Wang, Y.; Mikkelsen, L.P.; Pyka, G.; Withers, P.J. Time-Lapse Helical X-ray Computed Tomography (CT) Study of Tensile Fatigue Damage Formation in Composites for Wind Turbine Blades. <em>Materials</em> <strong>2018</strong>, <em>11</em>, 2340.</p>
<p>https://doi.org/10.3390/ma11112340</p>
<p>More information about the data and the material can be found in the paper above.</p>
<p> </p>
<p>If using the data here, please cite the above paper.<em> </em></p>
<p>Contact details for author: Ying Wang, ying.wang-4@manchester.ac.uk</p>
https://doi.org/10.5281/zenodo.1478688
oai:zenodo.org:1478688
Zenodo
https://zenodo.org/communities/mxif
https://doi.org/10.5281/zenodo.1478687
info:eu-repo/semantics/openAccess
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Time-lapse helical X-ray computed tomography (CT) data of tensile fatigue damage in GFRP
info:eu-repo/semantics/other
oai:zenodo.org:61394
2020-01-20T17:06:54Z
user-ipuom
user-mxif
openaire
Lionheart, William
2016-09-01
<p>We discuss several cases of what we call "Rich Tomography" problems in which more data is measured than a scalar for each ray. We give examples of infra red spectral tomography and Bragg edge neutron tomography in which the data is insufficient. For diffraction tomography of strain for polycrystaline materials we give an explicit reconstruction procedure. We go on to describe a way to find six independent rotation axes using Pascal's theorem of projective geometry</p>
This talk was given at an Inverse Problems seminar at University College London in 2013. Some of the material later appeared in Lionheart and Withers 2015 Diffraction Tomography of Strain http://iopscience.iop.org/article/10.1088/0266-5611/31/4/045005/meta
https://doi.org/10.5281/zenodo.61394
oai:zenodo.org:61394
Zenodo
https://zenodo.org/communities/ipuom
https://zenodo.org/communities/mxif
https://doi.org/
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rich tomography
infra red chemical species tomography
spectral tomography
Bragg edge tomography
x-ray strain tomography
transverse ray transform
Spectral and Diffraction Tomography
info:eu-repo/semantics/lecture
oai:zenodo.org:154515
2020-01-20T17:41:11Z
user-mxif
user-ccpi
openaire
Turner, Martin
Morris, Tim
Sandoval, Mario
Worthington, Sam
2016-09-05
<p>Any possible movement of a rigid body, no matter how complex, can be expressed as a combination of three translations and three rotations, the basic six degrees of freedom (6DoF) [LM10]. Volume visualisation as exploited in tomography packages, (e.g. Avizo (FEI), ImageJ, Paraview TomVis or Drishti) allow for multiple other parameters and other rigid bodies to be changed. Current users of these systems often have to exploit a single mouse and contrived keystrokes for even the simplest of data exploration and animation task.</p>
<p>Using a hand, a user can send and receive information through force/torque and displacement/rotation; which are translated by drivers for interpretation by the application. HCI studies classified input devices into two groups: isotonic (senses displacement or free movement with zero or constant resistance; e.g. the mouse) and isometric devices (senses force without perceptibly movement; e.g. a joystick) [Zha95]. Recently a new 6DoF device (Wing [Wor14]), allows one hand to combine both of these.</p>
<p>A new python driver, with improved calibration, has been written to link with the Drishti package [Lim12]; which has been evaluated with XCT users. Results showed user preference and comfort criteria (included expected cost), as well as timed specific tasks for comparative XCT viewing - creating a system that has potential ease of use and speed up in exploration and discovery. </p>
<p>Future work is planned to include multiple Wing devices allowing then for simultaneous interaction; for example manipulating both light parameters and object position; or changing clipping plane and object transparency.</p>
<p> </p>
Presented at ToScA 2016
https://doi.org/10.5281/zenodo.154515
oai:zenodo.org:154515
Zenodo
https://zenodo.org/communities/ccpi
https://zenodo.org/communities/mxif
https://doi.org/
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
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ToScA 2016, Tomography for Scientific Advancement symposium (ToScA) 2016, Bath, UK, 5-6 September 2016
6dof, HCI, Volume Visualisation, Interraction
6DoF Input Device Integration for XCT Volume Visualisation
info:eu-repo/semantics/conferencePoster
oai:zenodo.org:17608
2020-01-24T19:26:13Z
user-mxif
user-ccpi
user-ibsim
openaire_data
Mummery, Paul
Margetts, Lee
Dudarev, Sergei
Evans, Llion
2015-05-14
<p>Raw X-Ray CT data for CFC-Cu ITER monoblock mock-up. The monoblock was manufactured at Politecnico di Torino, Italy (Dr Valentina Casalegno) and X-ray tomography scanning was performed at the Manchester X-ray Imaging Facility, University of Manchester, UK (Dr Llion Evans).</p>
<p>This data was used for the publication Evans, Ll.M. et al. "Transient Thermal Finite Element Analysis of CFC-Cu ITER Monoblock Using X-ray Tomography Data", Fusion Engineering and Design 2015. DOI: 10.1016/j.fusengdes.2015.04.048</p>
https://doi.org/10.5281/zenodo.17608
oai:zenodo.org:17608
Zenodo
https://doi.org/10.1016/j.fusengdes.2015.04.048
https://zenodo.org/communities/ibsim
https://zenodo.org/communities/ccpi
https://zenodo.org/communities/mxif
https://doi.org/
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Carbon fibre composites
Copper
Laser flash
Joining
Thermal conductivity
X-ray tomography
Raw X-Ray CT data of CFC-Cu ITER monoblock mock-up
info:eu-repo/semantics/other
oai:zenodo.org:61409
2020-01-20T17:28:14Z
user-ipuom
user-mxif
user-ccpi
openaire
Moe, Yngve M.
Lloyd, Ryan
Tregidgo, Henry
Coban, Sophia B.
Gajjar,Parmesh
Behnsen, Julia
Turner, Martin
Lionheart, William R.B.
2016-09-02
<p>3-dimensional computerised tomography is usually reconstructed using the naïve Feldkamp-Davis-Kress algorithm or FDK, which is not an exact reconstruction algorithm. This caus-<br>
es image errors, or artefacts that appear out of the central slice, and are especially visible near edges between horizontal layers - this is demonstrated in Figure 1.<br>
To overcome these artefacts; one can perform multiple scans at different heights and combine the reconstructed volumes. However, exact reconstruction methods are necessary to<br>
remove them altogether. These algorithms will also reduce the scanning time which makes them very attractive. Such methods exist, and Alexander Katsevich provided an algo-<br>
rithm already in 2002[1]. His algorithm uses a helical scan-geometry, rotating the X-Ray source while moving it in parallel with the rotation axis - or, equivalently, scanning the ob-<br>
ject while rotating it and moving it parallel to its rotation axis. In this poster, we demonstrate that it is possible to perform and reconstruct such scans, with a Nikon XTEK scanner<br>
designed for circular scans.</p>
https://doi.org/10.5281/zenodo.61409
oai:zenodo.org:61409
Zenodo
https://zenodo.org/communities/ipuom
https://zenodo.org/communities/ccpi
https://zenodo.org/communities/mxif
https://doi.org/
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Creative Commons Attribution 4.0 International
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ToScA, Tomography for Scientific Advancement, Bath, UK, 6-7 September 2016
helical scan
cone beam CT
Katsevick
Nikon Xtek
artefacts
Implementing an exact algorithm for Helical CT:Removing the cone-beam artefacts
info:eu-repo/semantics/conferencePoster
oai:zenodo.org:2540509
2020-01-24T19:25:58Z
user-ipuom
user-mxif
user-ccpi
openaire_data
user-eu
Fisher, Sarah L
Holmes, Danny J
Jørgensen, Jakob S
Gajjar, Parmesh
Behnsen, Julia
Lionheart, William R B
Withers, Philip J
2019-01-09
<p>This data accompanies the publication</p>
<p> </p>
<p><strong>Laminography in the Lab: Imaging planar objects using a conventional x-ray CT scanner</strong></p>
<p>by Sarah L Fisher, Danny J Holmes, Jakob S Jørgensen, Parmesh Gajjar, Julia Behnsen, William R B Lionheart and Philip J Withers</p>
<p>Measurement Science and Technology, Vol. 30, No. 3, 2019</p>
<p><a href="https://doi.org/10.1088/1361-6501/aafcae">https://doi.org/10.1088/1361-6501/aafcae</a></p>
<p> </p>
<p> </p>
<p>The computed laminography (CL) and limited angle CT (LACT) data sets for the lego sample of the paper are provided, including both raw projection data and the final reconstructions, a total of 4 files for each of the CL and LACT cases. The files are (for CL)</p>
<p>CLProjectionData.zip: zip file with the raw projection images and meta data as produced by the Nikon instrument.</p>
<p>CLShadingCorrection.zip: zip file containing dark and flat field images.</p>
<p>CLreconstruction.mat: MATLAB mat-file with final CL reconstruction, size 798x798x200 voxels.</p>
<p>CLreconstruction.vol: Same CL reconstruction but in a generic binary file that for example simplify the loading of data into Avizo.</p>
<p> </p>
<p>The same set of files is available for the CT data. The CT data reconstruction has size 798x798x798.</p>
<p> </p>
<p>Accompanying MATLAB reconstruction code is available from</p>
<p><a href="https://github.com/sarahfisher1/Laminography">https://github.com/sarahfisher1/Laminography</a></p>
https://doi.org/10.5281/zenodo.2540509
oai:zenodo.org:2540509
Zenodo
https://zenodo.org/communities/ipuom
https://zenodo.org/communities/ccpi
https://zenodo.org/communities/mxif
https://zenodo.org/communities/eu
https://doi.org/10.5281/zenodo.2540508
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
x-ray
tomography
laminography
lego
Data for Laminography in the Lab: Imaging planar objects using a conventional x-ray CT scanner
info:eu-repo/semantics/other
oai:zenodo.org:16474
2020-05-06T12:34:00Z
user-ipuom
user-mxif
user-ccpi
openaire_data
Coban, S. B.
McDonald, S. A.
2015-03-30
<p><strong>SophiaBeads Dataset</strong> are acquired specifically for testing and comparing reconstruction methods for x-ray computed tomography. The sample is a plastic tube with a diameter of 25mm, filled with uniform Soda-Lime Glass (SiO2-Na2O) beads of diameters 2.5mm (with standard deviation 0.1mm). The sample has been scanned in the same conditions for each dataset, where the number of projections is halved after each batch scan (starting from 2048, down to 64 projections). This allows us to understand the effects of fewer projections, and develop algorithms that deliver quality results when the information content is low (i.e. faster scans or lower dose). </p>
<p> </p>
<p>These dataset are also suitable for developing and/or testing</p>
<ul>
<li>segmentation methods,</li>
<li>image or data correction techniques (e.g. centre of rotation),</li>
<li>forward and back project implementations, and</li>
<li>benchmarking user’s own code/method.</li>
</ul>
<p> </p>
<p>For the reconstruction and quantification examples, please see (will update with link to paper!)</p>
<p>To use these datasets for own research, please follow the technical report available via (http://eprints.ma.man.ac.uk/2290/), and the GitHub repository (http://sophilyplum.github.io/sophiabeads-datasets/). If publishing work with these datasets, <strong>the reader must cite the dataset <em>and</em> the codes separately</strong>. </p>
<p> </p>
<p>The dataset are taken using the <em>Nikon Custom Bay</em> machine (using a cone-beam geometry), located in the Manchester Xray Imaging Facility (www.mxif.manchester.ac.uk/resources/imaging-systems/nikon-custom-bay), by Sophia B. Coban and Samuel A. McDonald. </p>
<p> </p>
<p>Contact details for authors: </p>
<p>Sophia B. Coban: </p>
<ul>
<li>email: sophia.coban@gmail.com</li>
</ul>
<p>Samuel A. McDonald: </p>
<ul>
<li>email: sam.mcdonald@manchester.ac.uk</li>
</ul>
<p> </p>
<p>SophiaBeads Dataset Project Codes (DOI): https://zenodo.org/record/16539</p>
https://doi.org/10.5281/zenodo.16474
oai:zenodo.org:16474
Zenodo
https://doi.org/10.5281/zenodo.16539
https://doi.org/10.5281/zenodo.16539
https://zenodo.org/communities/ipuom
https://zenodo.org/communities/ccpi
https://zenodo.org/communities/mxif
https://doi.org/
info:eu-repo/semantics/openAccess
Creative Commons Attribution Share Alike 4.0 International
https://creativecommons.org/licenses/by-sa/4.0/legalcode
computed tomography
x-ray
cone beam
reconstruction algorithms
sophiabeads-dataset
segmentation
data correction
large dataset
SophiaBeads Dataset Project
info:eu-repo/semantics/other
oai:zenodo.org:4771123
2021-05-21T01:48:11Z
user-mxif
openaire_data
user-eu
Ying Wang
Philip J. Withers
2021-05-20
<p>This series of ultra-fast X-ray computed tomography datasets were acquired on the TOMCAT beamline at the Swiss Light Source by the composite group at Henry Moseley X-ray Imaging Facility (within the Henry Royce Institute @Manchester).</p>
<p>The experiment was designed to help understand the catastrophic failure of unidirectional fibre reinforced composites under compression, as part of Ying Wang's PhD project (<em>Damage Mechanisms Associated with Kink-Band Formation in Unidirectional Fibre Composites</em>) supervised by Prof. Philip J. Withers.</p>
<p>A notched unidirectional glass fibre-epoxy composite specimen was loaded in-situ under compression in a tension/compression rig developed at INSA-Lyon. An initial scan of the composite gauge section was acquired before loading (GFRP_Initial.zip). During the in-situ loading process, the composite specimen was imaged statically at 200 N (GFRP_Static_200N.zip) and 600 N (GFRP_Static_600N.zip), after which the acquisition mode was changed to continuous streaming in order to capture the final stages immediately leading up to failure, at 876 N (GFRP_Continuous_876N.zip), 893 N (GFRP_Continuous_893N.zip), 895 N (GFRP_Continuous_895N.zip), and right after collapse (at 79 N, GFRP_Failed.zip).</p>
<p>The CT acquisition speed attained 1 tomogram per second. The voxel size of the reconstructed CT data-sets is (1.1 μm)<sup>3</sup>.</p>
<p> </p>
<p><strong>For use of the data, please cite the DOI of the repository </strong><strong>and the relevant papers -</strong></p>
<p><em><strong>http://doi.org/10.5281/zenodo.2597497</strong> </em></p>
<p><em>Wang, Y., Emerson, M. J., Conradsen, K., Dahl, A. B., Dahl, V. A., Maire, E. and Withers, P. J. (2021). Evolution of Fibre Deflection Leading to Kink-band Formation in Unidirectional Glass Fibre/Epoxy Composite Under Axial Compression. Composites Science and Technology. (Under Review)</em></p>
<p><em>Emerson, M. J., Wang, Y., Withers, P. J., Conradsen, K., Dahl, A. B., and Dahl, V. A. (2018). Quantifying fibre reorientation during axial compression of a composite through time-lapse X-ray imaging and individual fibre tracking. Composites Science and Technology, 168, 47-54. </em></p>
<p><em>Wang, Y., Garcea, S. C., Lowe, T., Maire, E., Soutis, C. and Withers, P. J. (2016). Ultra-fast time-lapse synchrotron radiographic imaging of compressive failure in CFRP. In ECCM16-16th European Conference on Composite Materials, Munich, Germany.</em></p>
<p><em>Garcea, S. C. , Wang, Y. and Withers, P. J. (2018). X-ray computed tomography of polymer composites, Composites<br>
Science and Technology (156), 305-319.</em></p>
<p><em>Wang, Y., Garcea, S. C. and Withers, P. J. (2018). Computed Tomography of Composites in Comprehensive Composite<br>
Materials II (7), 101-118. Eds. Beaumont PWR, Zweben CH. Elsevier. </em></p>
We acknowledge the Engineering and Physical Science Research Council (EPSRC) for funding the Henry Moseley X-ray Imaging Facility within the Henry Royce Institute through grants (EP/F007906/1, EP/F001452/1, EP/I02249X, EP/M010619/1, EP/F028431/1, and EP/M022498/1). PJW acknowledges support from the European Research Council grant No 695638 CORREL-CT.
https://doi.org/10.5281/zenodo.4771123
oai:zenodo.org:4771123
Zenodo
https://zenodo.org/communities/mxif
https://zenodo.org/communities/eu
https://doi.org/10.5281/zenodo.2597497
info:eu-repo/semantics/openAccess
Creative Commons Attribution Non Commercial Share Alike 4.0 International
https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode
X-ray Computed Tomography
In-situ
High-speed
Ultra-fast time-lapse synchrotron radiation CT imaging of compressive failure in unidirectional glass fibre-epoxy composite
info:eu-repo/semantics/other
oai:zenodo.org:2597498
2021-05-20T19:58:10Z
user-mxif
openaire_data
user-eu
Ying Wang
Philip J. Withers
2019-03-27
<p>This series of ultra-fast X-ray computed tomography datasets were acquired on the TOMCAT beamline at the Swiss Light Source by the composite group at Henry Moseley X-ray Imaging Facility (within the Henry Royce Institute @Manchester).</p>
<p>The experiment was designed to help understand the catastrophic failure of unidirectional fibre reinforced composites under compression, as part of Ying Wang's PhD project (<em>Damage Mechanisms Associated with Kink-Band Formation in Unidirectional Fibre Composites</em>) supervised by Prof. Philip J. Withers.</p>
<p>A notched unidirectional glass fibre-epoxy composite specimen was loaded in-situ under compression in a tension/compression rig developed at INSA-Lyon. An initial scan of the composite gauge section was taken before loading (GFRP_Initial.zip), and the composite specimen was continuously loaded and imaged when approaching its failure (GFRP_Continuous_No0.zip and GFRP_Continuous_No12.zip).</p>
<p>The CT acquisition speed attained 1 tomogram per second. The voxel size of the reconstructed CT data-sets is (1.1 μm)<sup>3</sup>.</p>
<p>For use of the data, please cite the DOI of the repository and relevant papers -</p>
<p><em>Wang, Y., Garcea, S. C., Lowe, T., Maire, E., Soutis, C. and Withers, P. J. (2016). Ultra-fast time-lapse synchrotron radiographic imaging of compressive failure in CFRP. In ECCM16-16th European Conference on Composite Materials, Munich, Germany.</em></p>
<p><em>Emerson, M. J., Wang, Y., Withers, P. J., Conradsen, K., Dahl, A. B., and Dahl, V. A. (2018). Quantifying fibre reorientation during axial compression of a composite through time-lapse X-ray imaging and individual fibre tracking. Composites Science and Technology, 168, 47-54. </em></p>
<p>Please also acknowledge EPSRC and ERC support in the acknowledgements, including</p>
<p><em>Engineering and Physical Science Research Council (EPSRC) for funding the Henry Moseley X-ray Imaging Facility within the Henry Royce Institute through grants (EP/F007906/1, EP/F001452/1, EP/I02249X, EP/M010619/1, EP/F028431/1, and EP/M022498/1)</em></p>
<p><em> European Research Council grant No 695638 CORREL-CT.</em></p>
We acknowledge the Engineering and Physical Science Research Council (EPSRC) for funding the Henry Moseley X-ray Imaging Facility within the Henry Royce Institute through grants (EP/F007906/1, EP/F001452/1, EP/I02249X, EP/M010619/1, EP/F028431/1, and EP/M022498/1). PJW acknowledges support from the European Research Council grant No 695638 CORREL-CT.
https://doi.org/10.5281/zenodo.2597498
oai:zenodo.org:2597498
Zenodo
https://zenodo.org/communities/mxif
https://zenodo.org/communities/eu
https://doi.org/10.5281/zenodo.2597497
info:eu-repo/semantics/openAccess
Creative Commons Attribution Non Commercial Share Alike 4.0 International
https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode
X-ray Computed Tomography
In-situ
High-speed
Ultra-fast time-lapse synchrotron radiation CT imaging of compressive failure in unidirectional glass fibre-epoxy composite
info:eu-repo/semantics/other
oai:zenodo.org:1204088
2020-01-24T19:25:08Z
user-mxif
user-ccpi
openaire_data
Parmesh Gajjar
Jakob S. Jorgensen
Jose R. A. Godinho
Chris G. Johnson
Andrew Ramsey
Philip J. Withers
2018-03-20
<p>These are the accompanying datasets from the paper "<strong>New software protocols for enabling </strong><strong>laboratory based</strong><strong> temporal CT</strong>". There are two datasets: the germination of a mung bean captured using 54 uninterrupted time-lapse tomograms, and the precipitation of barite in a porous media with continuous golden-ratio projections.</p>
<p>The data was collected using software extensions written for Nikon Metrology CT systems using IPC. These software extensions implemented the protocols highlighted in the paper, and can be found in the following GitHub repositories:</p>
<p>Uninterrupted Time-Lapse CT: <a href="https://github.com/parmeshgajjar/TemporalCT-TimeLapse.Uninterrupted.git">https://github.com/parmeshgajjar/TemporalCT-TimeLapse.Uninterrupted.git</a></p>
<p>Continuous Golden Ratio Acquisition CT: <a href="https://github.com/parmeshgajjar/TemporalCT-ContinuousGR.Acqusition">https://github.com/parmeshgajjar/TemporalCT-ContinuousGR.Acqusition</a></p>
<p>The reconstructions were performed using the ASTRA toolbox with MATLAB. The code for this can be found at the following GitHub repository: <a href="https://github.com/jakobsj/TemporalCT-ContinuousGR.Reconstruction">https://github.com/jakobsj/TemporalCT-ContinuousGR.Reconstruction</a></p>
The authors would like to thank Tom Slater and James Carr for insightful discussions and support. PG
acknowledges support from EPSRC platform grants EP/M010619/1, EP/M022498/1 and EP/J010456/1
whilst JJ acknowledges support from EPSRC grant EP/P02226X/1. The shear cell was developed as part
of the EPSRC Doctoral Training Grant EP/K502947/1. Beamtime was kindly provided by the Henry Mose-
ley X-ray Imaging Facility, which was established through EPSRC grants EP/F007906/1, EP/I02249X/1
and EP/F028431/1. Funding was also provided through the Henry Royce Institute, established through
EPSRC grants EP/R00661X/1, EP/P025498/1 and EP/P025021/1.
https://doi.org/10.5281/zenodo.1204088
oai:zenodo.org:1204088
Zenodo
https://zenodo.org/communities/ccpi
https://zenodo.org/communities/mxif
https://doi.org/10.5281/zenodo.1204087
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
Review of Scientific Instruments, (2018-03-20)
X-ray CT, X-ray Computed Tomography, 4D, Time-lapse imaging, Software protocols
New software protocols for enabling laboratory based temporal CT
info:eu-repo/semantics/other
oai:zenodo.org:4157615
2020-11-22T22:39:38Z
user-mxif
user-ccpi
openaire_data
Ryan Warr
Christopher Egan
Evangelos Papoutsellis
Jakob Sauer Jørgensen
Evelina Ametova
Robert Cernik
Philip J. Withers
2020-11-21
<p><strong>General data description:</strong></p>
<p>This is a hyperspectral (energy-resolved) X-ray CT projection data set of a mineralised ore sample with small gold and galena deposits. It was acquired in a laboratory micro-CT scanner with an energy-sensitive HEXITEC detector in the Henry Moseley X-ray Imaging Facility at The University of Manchester.</p>
<p>The data included contains all the relevant files required for reconstruction, following a hyperspectral scan of a mineralised ore sample. The sample contains a number of mineral phases, of varying concentration, distributed throughout. Some phases (including gold, and lead-based Galena) produce unique absorption edges, which act as spectral identifiers that can be measured by an energy-sensitive detector.</p>
<p><strong>File descriptions:</strong></p>
<p>The data set consists of one .txt file and three .mat (MATLAB) data files.</p>
<p>Au_rock_scan_geometry.txt gives a breakdown of the full sample and detector geometry used when acquiring the raw projections. The number of horizontal detector pixels accounts for the fact that a set of 5 tiled scans of the sample were collected and later stitched together.</p>
<p>Au_rock_sinogram_full.mat contains the full 4D sinogram constructed following flat-field normalisation of the raw projection data. The data matrix contains the total number of energy channels acquired during scanning, as well as the conventional elements of vertical/horizontal detector pixel number and total projection angles.</p>
<p>commonX.mat provides a direct conversion between the energy channels, and the energies (in keV) that they correspond to, following a calibration procedure prior to scanning.</p>
<p>FF.mat contains the 4D flatfield data acquired when no sample was present. This data was used to normalise the projection datasets, as the sinogram was constructed.</p>
https://doi.org/10.5281/zenodo.4157615
oai:zenodo.org:4157615
Zenodo
https://zenodo.org/communities/ccpi
https://zenodo.org/communities/mxif
https://doi.org/10.5281/zenodo.4157614
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
Spectral CT, hyperspectral imaging, tomographic reconstruction, projection data
Hyperspectral X-ray CT data set of mineralised ore sample with Au and Pb deposits
info:eu-repo/semantics/other
oai:zenodo.org:16539
2020-01-25T07:26:45Z
user-ipuom
user-mxif
user-ccpi
software
Coban, S. B.
2015-04-01
<p>The initial release of the codes, to be used for the SophiaBeads Dataset Project.</p>
<p>The codes are <em>essential</em> to work with the SophiaBeads Dataset. The release contains scripts for loading the dataset, pre-reconstruction steps, and a reconstruction algorithm (cgls_XTek) as a template.</p>
<p>More information about this release can be found on the GitHub project page.</p>
<p> </p>
<p>SophiaBeads Dataset Project: https://zenodo.org/record/16474</p>
https://doi.org/10.5281/zenodo.16539
oai:zenodo.org:16539
Zenodo
https://github.com/Sophilyplum/sophiabeads-datasets/tree/v1.0
https://doi.org/10.5281/zenodo.16474
https://doi.org/10.5281/zenodo.16474
http://eprints.ma.man.ac.uk/2290/
http://eprints.ma.man.ac.uk/2290/
https://zenodo.org/communities/ipuom
https://zenodo.org/communities/ccpi
https://zenodo.org/communities/mxif
https://doi.org/10.5281/zenodo.593371
info:eu-repo/semantics/openAccess
Other (Attribution)
computed tomography
x-ray
cone beam
sophiabeads-dataset
software
reconstruction algorithms
github
codes
SophiaBeads Dataset Project Codes
info:eu-repo/semantics/other
oai:zenodo.org:18123
2020-01-20T17:01:10Z
user-ipuom
user-mxif
openaire
Lionheart, William
Withers, Philip
Desai, Naeem
Schmidt, Søren
2015-05-28
<p>In this conference talk we consider the transverse ray transform on symmetric rank 2 tensor fields in three dimensional Euclidean space and give an explicit inversion formula for complete data and for data for lines parallel to three orthogonal directions. We show how this can be used to determine the strain in a polycrystalline material using a<br />
synchrotron x-ray source.<br />
We go on to consider the problem of determination of a magnetic field from neutron spin tomography data and show that this problem reduces to a non-abelian ray transform in the plane and that the solution is unique for sufficiently smooth magnetic fields.</p>
https://doi.org/10.5281/zenodo.18123
oai:zenodo.org:18123
Zenodo
https://zenodo.org/communities/ipuom
https://zenodo.org/communities/mxif
https://doi.org/
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
AIP 2015, Applied Inverse Problems 2015, Helsinki, Finland, 25-29 May 2015
tensor tomography
non-abelian tomography
transverse ray transform
x-ray strain tomography
neutron spin tomography
Applications of tensor and non-Abelian ray transforms
info:eu-repo/semantics/lecture
oai:zenodo.org:61396
2020-01-20T16:22:33Z
user-mxif
openaire
Gajjar, Parmesh
Mcdonald, Sam
Jørgensen, Jakob S.
Behnsen, Julia
Johnson, Chris
Gray, Nico
Lionheart, William
Turner, Martin
Withers, Philip J
2016-09-02
<p>X-Ray CT machines have been powerful tools for complete 3D imaging and analysis of medical specimens and industrial artefacts, ranging from the scanning of steam location and aeroplane jet engines to parasitic bacteria. Technological advances have meant that the cost of these machines is now affordable to many institutions. But, despite the wide scope and increased availability, most machines are restricted to being used as “black-boxes”, with the user limited to only those routines provided by the<br />
manufacturers.</p>
<p>One unique feature of the 320/225 kV Nikon XTEK bay is its ability to be “hacked”, namely programmed in a custom manner by the user. The Nikon Inspect-X software comes with a graphical user interface that<br />
allows the user to perform 2D and 3D scans, inspections, along with many options such regions of interest, shading corrections, automatic reconstruction and batch processing. The Inspect-X software also<br />
contains a module enabling the entire system to be controlled through Visual Basic for Applications (VBA). The VBA editor is housed within the Inspect-X software, and is the same VBA editor found in<br />
Microsoft Word, meaning that generic code can be developed away from the CT machine. Each aspect of the X-Ray source, manipulator and image processing pipeline can be accessed using individual functions,<br />
allowing the user to build up a series of simple macros for performing certain tasks, e.g. switch x-rays on<br />
and off, capture and save an image or rotate the manipulator by a set angle. These simple macros can<br />
then be combined together in complex applications. The VBA programming capability of the 320/225 kV<br />
Nikon XTEK bay demonstrates the nearly unlimited potential of lab-based X-Ray CT systems to resolve a<br />
whole range of new complex scientific and industrial problems.</p>
Poster delivered at TOSCA, Bath Sept 2016
https://doi.org/10.5281/zenodo.61396
oai:zenodo.org:61396
Zenodo
https://zenodo.org/communities/mxif
https://doi.org/
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
ToScA, Tomography for Scientific Advancement, Bath, UK, 6-7 September 2016
x-ray tomography
limited angle
helical scan
granular shear box
Beyond a black box: “Hacking” a Nikon Metrology X-Ray CT Machine
info:eu-repo/semantics/conferencePoster
oai:zenodo.org:4737399
2022-01-06T15:37:34Z
user-mxif
user-ccpi
openaire_data
Ryan Warr
Jakob Sauer Jørgensen
Evangelos Papoutsellis
Evelina Ametova
Robert Cernik
Philip J. Withers
2020-12-18
<p><strong>General Data description:</strong></p>
<p>This is a set of two hyperspectral (energy-resolved) X-ray CT projection datasets of a multi-phase phantom. It was acquired in a custom-built, laboratory micro-CT scanner with an energy-sensitive HEXITEC detector in the Henry Moseley X-ray Imaging Facility at The University of Manchester.</p>
<p>The following data contains all the files necessary for reconstruction, following two hyperspectral scans of a metal, multi-phase phantom. The phantom consists of an external aluminium cylinder, with three holes, each filled with a different metal-based powder (CeO<sub>2</sub>, ZnO, Fe). Each powder provides a unique attenuation signal, with CeO<sub>2</sub> in particular producing a distinct spectral marker which can be measured by an energy-sensitive detector. Two identical scans were acquired, with only the exposure time per projection changed.</p>
<p><strong>File descriptions:</strong></p>
<p>Contained is an image (.jpg) of the sample, along with five MATLAB (.mat) data files, as well as a single text (.txt) file. Where necessary, the files have been named to match the dataset they belong to, based on the different exposure times used for each dataset.</p>
<p>Phantom_design_measurements.jpg contains a photograph of the physical phantom, combined with a diagram showing full sample measurements.</p>
<p>Powder_phantom_scan_geometry.txt gives a breakdown of the full sample and detector geometry used when acquiring the raw projections for both scans.</p>
<p>powder_phantom_30s_sinogram.mat contains the 4D sinogram constructed following flatfield normalisation of the raw projection data, where an exposure time of 30 s was used for each projection. The 4D array contains the total number of energy channels acquired during scanning, followed by vertical and horizontal pixel number, and finally total projections angles acquired during scanning. The total number of channels in the file is 400, however relevant data is stored only up to channel 220, with the remaining channels containing noise and scatter, and therefore can be discarded. No corrections or filters have been applied to the data.</p>
<p>powder_phantom_180s_sinogram.mat is the 4D sinogram for the dataset, when exposure times of 180 s were used for each projection, following flatfield normalisation. A discontinuity occurs at projection 137 due to an interruption in the scan procedure. The total number of channels in the file is 400, however relevant data is stored only up to channel 220, with the remaining channels containing noise and scatter, and therefore can be discarded. No corrections or filters have been applied to the data.</p>
<p>Energy_axis.mat provides a direct conversion between the energy channels, and the energies (in keV) that they correspond to, following a calibration procedure prior to scanning. This is the same for both datasets.</p>
<p>FF_30s.mat contains the 4D flatfield data acquired when no sample was present, in the case of 30 s exposure times. This data was used to normalise the projection datasets, as the sinogram was constructed. The full 400 channels are included.</p>
<p>FF_180s.mat contains the 4D flatfield data for the dataset where 180 s exposure times were used. The full 400 channels are included.</p>
https://doi.org/10.5281/zenodo.4737399
oai:zenodo.org:4737399
eng
Zenodo
https://zenodo.org/communities/ccpi
https://zenodo.org/communities/mxif
https://doi.org/10.5281/zenodo.4354815
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
Hyperspectral
Phantom
X-ray CT
Hyperspectral X-ray CT datasets of an aluminium phantom containing three metal-based powders
info:eu-repo/semantics/other
oai:zenodo.org:4354816
2022-01-06T15:37:34Z
user-mxif
user-ccpi
openaire_data
Ryan Warr
Jakob Sauer Jørgensen
Evangelos Papoutsellis
Evelina Ametova
Robert Cernik
Philip J. Withers
2020-12-18
<p><strong>General Data description:</strong></p>
<p>This is a set of two hyperspectral (energy-resolved) X-ray CT projection datasets of a multi-phase phantom. It was acquired in a custom-built, laboratory micro-CT scanner with an energy-sensitive HEXITEC detector in the Henry Moseley X-ray Imaging Facility at The University of Manchester.</p>
<p>The following data contains all the files necessary for reconstruction, following two hyperspectral scans of a metal, multi-phase phantom. The phantom consists of an external aluminium cylinder, with three holes, each filled with a different metal-based powder (CeO<sub>2</sub>, ZnO, Fe). Each powder provides a unique attenuation signal, with CeO<sub>2</sub> in particular producing a distinct spectral marker which can be measured by an energy-sensitive detector. Two identical scans were acquired, with only the exposure time per projection changed.</p>
<p><strong>File descriptions:</strong></p>
<p>Contained is an image (.jpg) of the sample, along with five MATLAB (.mat) data files, as well as a single text (.txt) file. Where necessary, the files have been named to match the dataset they belong to, based on the different exposure times used for each dataset.</p>
<p>Phantom_design_measurements.jpg contains a photograph of the physical phantom, combined with a diagram showing full sample measurements.</p>
<p>Powder_phantom_scan_geometry.txt gives a breakdown of the full sample and detector geometry used when acquiring the raw projections for both scans.</p>
<p>powder_phantom_30s_sinogram_full.mat contains the full 4D sinogram constructed following flatfield normalisation of the raw projection data, where an exposure time of 30 s was used for each projection. The 4D array contains the total number of energy channels acquired during scanning, followed by vertical and horizontal pixel number, and finally total projections angles acquired during scanning.</p>
<p>powder_phantom_180s_sinogram_full.mat is the full 4D sinogram for the dataset, when exposure times of 180 s were used for each projection, following flatfield normalisation. A discontinuity occurs at projection 137 due to an interruption in the scan procedure.</p>
<p>Energy_axis.mat provides a direct conversion between the energy channels, and the energies (in keV) that they correspond to, following a calibration procedure prior to scanning. This is the same for both datasets.</p>
<p>FF_30s.mat contains the 4D flatfield data acquired when no sample was present, in the case of 30 s exposure times. This data was used to normalise the projection datasets, as the sinogram was constructed.</p>
<p>FF_180s.mat contains the 4D flatfield data for the dataset where 180 s exposure times were used</p>
https://doi.org/10.5281/zenodo.4354816
oai:zenodo.org:4354816
eng
Zenodo
https://zenodo.org/communities/ccpi
https://zenodo.org/communities/mxif
https://doi.org/10.5281/zenodo.4354815
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
Hyperspectral
Phantom
X-ray CT
Hyperspectral X-ray CT datasets of an aluminium phantom containing three metal-based powders
info:eu-repo/semantics/other
oai:zenodo.org:5825464
2022-01-07T13:48:49Z
user-mxif
user-ccpi
openaire_data
Ryan Warr
Jakob Sauer Jørgensen
Evangelos Papoutsellis
Evelina Ametova
Robert Cernik
Philip J. Withers
2022-01-06
<p><strong>General Data description:</strong></p>
<p>This is a set of two hyperspectral (energy-resolved) X-ray CT projection datasets of a multi-phase phantom. It was acquired in a custom-built, laboratory micro-CT scanner with an energy-sensitive HEXITEC detector in the Henry Moseley X-ray Imaging Facility at The University of Manchester.</p>
<p>The following data contains all the files necessary for reconstruction, following two hyperspectral scans of a metal, multi-phase phantom. The phantom consists of an external aluminium cylinder, with three holes, each filled with a different metal-based powder (CeO<sub>2</sub>, ZnO, Fe). Each powder provides a unique attenuation signal, with CeO<sub>2</sub> in particular producing a distinct spectral marker which can be measured by an energy-sensitive detector. Two identical scans were acquired, with only the exposure time per projection changed.</p>
<p>Note: Zenodo Version 2 of this dataset contains the incorrect version of the 180s, 180 projection phantom dataset, if wishing to analyse the dataset used in the associated hyperspectral paper. This version (Version 3) contains the correct dataset from the paper.</p>
<p><strong>File descriptions:</strong></p>
<p>Contained is an image (.jpg) of the sample, along with five MATLAB (.mat) data files, as well as a single text (.txt) file. Where necessary, the files have been named to match the dataset they belong to, based on the different exposure times used for each dataset.</p>
<p>Phantom_design_measurements.jpg contains a photograph of the physical phantom, combined with a diagram showing full sample measurements.</p>
<p>Powder_phantom_scan_geometry.txt gives a breakdown of the full sample and detector geometry used when acquiring the raw projections for both scans.</p>
<p>Powder_phantom_30s_30Proj_sinogram.mat contains the 4D sinogram constructed following flatfield normalisation of the raw projection data, where an exposure time of 30 s was used for each projection. The 4D array contains the total number of energy channels acquired during scanning, followed by vertical and horizontal pixel number, and finally total projections angles acquired during scanning. The total number of channels in the file is 200.</p>
<p>Powder_phantom_180s_180Proj_sinogram.mat is the 4D sinogram for the dataset, when exposure times of 180 s were used for each projection, following flatfield normalisation. A discontinuity occurs at projection 137 due to an interruption in the scan procedure. The total number of channels in the file is 200.</p>
<p>Energy_axis.mat provides a direct conversion between the energy channels, and the energies (in keV) that they correspond to, following a calibration procedure prior to scanning. This is the same for both datasets.</p>
<p>FF_30s.mat contains the 4D flatfield data acquired when no sample was present, in the case of 30 s exposure times. This data was used to normalise the projection datasets, as the sinogram was constructed. The first 200 channels are included.</p>
<p>FF_180s.mat contains the 4D flatfield data for the dataset where 180 s exposure times were used. The first 200 channels are included.</p>
https://doi.org/10.5281/zenodo.5825464
oai:zenodo.org:5825464
eng
Zenodo
https://doi.org/10.1038/s41598-021-00146-4
https://zenodo.org/communities/ccpi
https://zenodo.org/communities/mxif
https://doi.org/10.5281/zenodo.4354815
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
Hyperspectral
Phantom
X-ray CT
Hyperspectral X-ray CT datasets of an aluminium phantom containing three metal-based powders
info:eu-repo/semantics/other
oai:zenodo.org:5826212
2022-01-07T13:48:49Z
user-mxif
user-ccpi
openaire_data
Ryan Warr
Jakob Sauer Jørgensen
Evangelos Papoutsellis
Evelina Ametova
Stephan Handschuh
Robert Cernik
Philip J. Withers
2022-01-06
<p><strong>General Data description:</strong></p>
<p>This is a hyperspectral (energy-resolved) X-ray CT projection dataset of a lizard head sample, stained with an iodine contrast agent. It was acquired in a custom-built, laboratory micro-CT scanner with an energy-sensitive HEXITEC detector in the Henry Moseley X-ray Imaging Facility at The University of Manchester.</p>
<p>The following data contains all the files necessary for reconstruction, after a hyperspectral scan was taken of a single, iodine-stained lizard head sample. The iodine contrast agent provided a spectral marker, measured by an energy-sensitive detector, which may be used for spatial mapping and segmentation of stained soft tissue regions.</p>
<p><strong>File descriptions:</strong></p>
<p>Contained are four MATLAB (.mat) data files, as well as a single text (.txt) file.</p>
<p>Lizard_head_scan_parameters.txt provides the full sample and detector geometry of the scan acquisition.</p>
<p>lizard_180Proj_noSupp_1_180.mat contains the full 4D sinogram constructed following flatfield normalisation of the raw projection data. The 4D array contains the total number of energy channels acquired during scanning, vertical and horizontal pixel number, and total projections angles acquired. The data provided is prior to application of any post-processing filters. The first 180 energy channels are included.</p>
<p>lizard_180Proj_Supp_1_180.mat contains the full 4D sinogram constructed following flatfield normalisation of the raw projection data. This dataset is identical to the .mat file above, however here we have also applied a ring-reduction filter, using a wavelet-based Fourier filter which suppresses the presence of ring artefacts in every energy channel. The first 180 energy channels are included.</p>
<p>Energy_axis.mat provides a direct conversion between the energy channels, and the energies (in keV) that they correspond to, following a calibration procedure prior to scanning.</p>
<p>FF.mat contains the 4D flatfield data acquired when no sample was present. This data was used to normalise the projection datasets, as the sinogram was constructed. The first 180 energy channels are included.</p>
https://doi.org/10.5281/zenodo.5826212
oai:zenodo.org:5826212
eng
Zenodo
https://doi.org/10.1038/s41598-021-00146-4
https://zenodo.org/communities/ccpi
https://zenodo.org/communities/mxif
https://doi.org/10.5281/zenodo.4352943
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
Hyperspectral
Bioimaging
X-ray CT
Hyperspectral X-ray CT dataset of a single, iodine-stained lizard head sample
info:eu-repo/semantics/other
oai:zenodo.org:5013680
2022-01-06T21:48:22Z
user-mxif
user-ccpi
openaire_data
Ryan Warr
Jakob Sauer Jørgensen
Evangelos Papoutsellis
Evelina Ametova
Stephan Handschuh
Robert Cernik
Philip J. Withers
2021-05-04
<p><strong>General Data description:</strong></p>
<p>This is a hyperspectral (energy-resolved) X-ray CT projection dataset of a lizard head sample, stained with an iodine contrast agent. It was acquired in a custom-built, laboratory micro-CT scanner with an energy-sensitive HEXITEC detector in the Henry Moseley X-ray Imaging Facility at The University of Manchester.</p>
<p>The following data contains all the files necessary for reconstruction, after a hyperspectral scan was taken of a single, iodine-stained lizard head sample. The iodine contrast agent provided a spectral marker, measured by an energy-sensitive detector, which may be used for spatial mapping and segmentation of stained soft tissue regions.</p>
<p><strong>File descriptions:</strong></p>
<p>Contained are three MATLAB (.mat) data files, two HDF5 (.h5) files, and a single text (.txt) file.</p>
<p>Lizard_head_scan_parameters.txt provides the full sample and detector geometry of the scan acquisition.</p>
<p>lizard_head_sinogram_full.mat contains the full 4D sinogram constructed following flatfield normalisation of the raw projection data. The 4D array contains the total number of energy channels acquired during scanning, followed by vertical and horizontal pixel number, and finally total projections angles acquired. The data provided is prior to application of any post-processing filters. The full set of 200 energy channels are included.</p>
<p>Energy_axis.mat provides a direct conversion between the energy channels, and the energies (in keV) that they correspond to, following a calibration procedure prior to scanning.</p>
<p>FF.mat contains the 4D flatfield data acquired when no sample was present. This data was used to normalise the projection datasets, as the sinogram was constructed. The full set of 200 energy channels are included.</p>
<p>Lizard_Sino_1_200.h5 contains the full 4D sinogram, with all 200 channels, but in an h5 format to enable easier data reading. Here the sinogram has also had a ring-reduction filter applied, using a wavelet-based Fourier filter which suppresses the presence of ring artefacts in every energy channel.</p>
<p>Lizard_Sino_100_140.h5 contains a cropped version of the 4D sinogram, with 40 channels taken in the channel range 100 to 140, stored in an h5 format to enable easier data reading. These 40 channels are known to contain the key spectral information regarding the K-edge of the iodine contrast agent. Here the sinogram has also had a ring-reduction filter applied, using a wavelet-based Fourier filter which suppresses the presence of ring artefacts in every energy channel.</p>
https://doi.org/10.5281/zenodo.5013680
oai:zenodo.org:5013680
eng
Zenodo
https://zenodo.org/communities/ccpi
https://zenodo.org/communities/mxif
https://doi.org/10.5281/zenodo.4352943
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
Hyperspectral
Bioimaging
X-ray CT
Hyperspectral X-ray CT dataset of a single, iodine-stained lizard head sample
info:eu-repo/semantics/other
oai:zenodo.org:18414
2020-01-24T19:26:26Z
user-mxif
user-ccpi
user-ibsim
openaire_data
Mummery, Paul
Margetts, Lee
Dudarev, Sergei
Evans, Llion
2015-05-15
<p>Raw X-Ray CT data for CFC-Cu_GS laser flash coupon. The coupon was manufactured at Politecnico di Torino, Italy (Dr Valentina Casalegno) and X-ray tomography scanning was performed at the Manchester X-ray Imaging Facility, University of Manchester, UK (Dr Llion Evans).</p>
<p>This data was used for the publications:</p>
<p> - Evans, Ll.M. et al. "Thermal characterisation of ceramic/metal joining techniques for fusion applications using X-ray tomography", Fusion Engineering and Design, Volume 89, Issue 6, June 2014, Pages 826-836, http://dx.doi.org/10.1016/j.fusengdes.2014.05.002.</p>
<p> - Evans, Ll.M. et al. "Transient Thermal Finite Element Analysis of CFC-Cu ITER Monoblock Using X-ray Tomography Data", Fusion Engineering and Design 2015, DOI: 10.1016/j.fusengdes.2015.04.048.</p>
https://doi.org/10.5281/zenodo.18414
oai:zenodo.org:18414
Zenodo
https://doi.org/10.1016/j.fusengdes.2014.05.002
https://doi.org/10.1016/j.fusengdes.2015.04.048
https://zenodo.org/communities/ibsim
https://zenodo.org/communities/ccpi
https://zenodo.org/communities/mxif
https://doi.org/
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
Carbon fibre composites
Copper
Laser flash
Joining
Thermal conductivity
X-ray tomography
Raw X-Ray CT data of CFC-Cu_GS laser flash coupon
info:eu-repo/semantics/other