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Dataset results
5 results for “tomography, CT, data”
X-ray tomography (CT) image data of tungsten fusion energy heat exchange components
<p>X-ray tomography (CT) image data of tungsten fusion energy heat exchange components.</p> <p>The dataset includes images of four samples:</p> <ul> <li>CCFE_MB_ROI (Culham Centre for Fusion Energy thermal break concept monoblock, region of interest sample)</li> <li>IPP_Wf-Cu (Max-Planck-Institut für Plasmaphysik tungsten fibre / copper matrix coolant pipe)</li> <li>ITER_HHFT_ROI (ITER reference monoblock which has undergone high heat flux testing, region of interest sample)</li> <li>ITER_MB_ROI (ITER reference monoblock, region of interest sample)</li> </ul> <p>This data was used originally for the following publication (please cite if re-using the data) where further details on the data may be obtained:</p> <p>Ll.M. Evans, L. Margetts, P.D. Lee, C.A.M. Butler, E. Surrey, “Image based in silico characterisation of the effective thermal properties of a graphite foam”, Carbon, Vol. 143, pp. 542-558, 2018. <a href="https://doi.org/10.1016/j.carbon.2018.10.031">https://doi.org/10.1016/j.carbon.2018.10.031</a></p> <p>Each of the sample directories include reconstructed slices in Tiff format. To visualise the 3D volume use software such as ImageJ (https://imagej.net/Fiji/Downloads). CCFE_MB_ROI also includes raw radiographs; scan & reconstruction parameter settings file.</p> <p>A Neutron CT version of this data is available for comparison: <a href="https://doi.org/10.5281/zenodo.3533418">https://doi.org/10.5281/zenodo.3533418</a></p> <p>Image-based simulation (IBSim) meshes were generated directly from these datasets: <a href="https://doi.org/10.5281/zenodo.3533422">https://doi.org/10.5281/zenodo.3533422</a></p>
Neutron tomography (CT) image data of tungsten fusion energy heat exchange components
<p>Neutron tomography (CT) image data of tungsten fusion energy heat exchange components.</p> <p>The dataset includes three sets of images:</p> <ul> <li>ITER_171T-WA-0002_MB (ITER reference monoblock)</li> <li>CCFE_ThBr_MB (Culham Centre for Fusion Energy thermal break concept monoblock)</li> <li>ROIsamples_Stack (A stack of four region of interest samples*)</li> </ul> <p>The region of interest samples within the stack are as below:</p> <ul> <li>CCFE_ThBr_ROI (Culham Centre for Fusion Energy thermal break concept monoblock)</li> <li>IPP_Wf-Cu_p5_s1 (Max-Planck-Institut für Plasmaphysik tungsten fibre / copper matrix coolant pipe)</li> <li>ITER_HHFT_ROI (ITER reference monoblock which has undergone high heat flux testing)</li> <li>ITER_17IT-WA-0002_ROI (ITER reference monoblock)</li> </ul> <p>This data was used originally for the following publication (please cite if re-using the data) where further details on the data may be obtained:</p> <p>Ll.M. Evans, L. Margetts, P.D. Lee, C.A.M. Butler, E. Surrey, “Image based in silico characterisation of the effective thermal properties of a graphite foam”, Carbon, Vol. 143, pp. 542-558, 2018. <a href="https://doi.org/10.1016/j.carbon.2018.10.031">https://doi.org/10.1016/j.carbon.2018.10.031</a></p> <p>Each of the sample directories include reconstructed slices in Tiff format. To visualise the 3D volume use software such as ImageJ (https://imagej.net/Fiji/Downloads).</p> <p>CCFE_ThBr_ROI and ROIsamples_Stack include raw radiographs; dark and flat field images; scan & reconstruction parameter settings file.</p> <p>ITER_171T-WA-0002_MB includes data relating to the modulation transfer function (MTF) measurement.</p> <p>An X-Ray CT version of the ROI data is available for comparison: <a href="https://doi.org/10.5281/zenodo.3533420">https://doi.org/10.5281/zenodo.3533420</a></p> <p>Image-based simulation (IBSim) meshes were generated directly from these datasets: <a href="https://doi.org/10.5281/zenodo.3533422">https://doi.org/10.5281/zenodo.3533422</a></p>
Time-lapse helical X-ray computed tomography (CT) data of tensile fatigue damage in GFRP
<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>
CT Data of a Pen-Spring: Application to Under-Sampled Dynamic X-ray Tomography
<p>This is the documentation of Computed Tomography (CT) data of a pen-spring. It can be freely used for scientific purposes with appropriate references to the data and to this document in https://arxiv.org/abs/1907.01871. The provided data set includes the X-ray sinograms finalSino of a single 2D slice from a different height of the spring. The finalSino was obtained from a measured 10-projection or 100-projection sinogram using fan-beam geometry<br> by down-sampling and taking logarithms. The data set includes also those original measured sinograms and corresponding measurement matrices.</p>
Computed Tomography (CT) and Lung Function Data Collection for Computational Fluid Dynamics (CFD) in Chronic Obstructive Pulmonary Disease (COPD) Patients
ClinicalTrials.gov study NCT00966459. IPD Sharing: Not stated. Countries: 1. Publications: 0.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.