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opencc-by-4.0Oct 2020View details →

X-ray computed tomography of bedded halite and halite crystals from the Bonneville Salt Flats

X-ray computed tomography of bedded halite and halite crystals from the Bonneville Salt Flats, Utah.

opencc-by-4.0Aug 2017View details →

Ex-situ X-ray computed tomography data for a non-crimp fabric based fibre composite under fatigue loading

Ex-situ X-ray CT fatigue testing data sets published as a data in brief: "Ex-situ X-ray computed tomography data for a non-crimp fabric based fibre composite under fatigue loading", Data in brief, 2017, doi.org/10.1016/j.dib.2017.10.074. Together with the following article: K. M. Jespersen and L. P. Mikkelsen, “Three dimensional fatigue damage evolution in non-crimp glass fibre fabric based composites used for wind turbine blades,” Compos. Sci. Technol. (In press), 2017, 10.1016/j.compscitech.2017.10.004.

FIGURE 4 in Benefits and limits of x-ray micro-computed tomography for visualization of colonization and bioerosion of shelled organisms

FIGURE 4. Ordovician bryozoan colony. One-half of hemispherical bryozoan, interior of object, bearing probably oldest boring attributable to ichnogenus Entobia Bronn, 1837. Besides semi-radial tunnels and exploratory threads, three bulbous chambers discovered near the center of the hemisphere. Darriwilian (middle Ordovician), Khrevitsa locality, St. Petersburg Region, Russia. Scale bar equals 1 cm.

FIGURE 7 in Benefits and limits of x-ray micro-computed tomography for visualization of colonization and bioerosion of shelled organisms

FIGURE 7. Three-dimensional visualization of a shell of the recent Foraminifera Amphistegina sp. illustrating the potential of micro-CT in investigations of recent marine shelled organisms. (A) A surface view of the whole shell. (B) A transversal section through the whole shell (C, D) Details of the shells´s surface.

FIGURE 5 in Benefits and limits of x-ray micro-computed tomography for visualization of colonization and bioerosion of shelled organisms

FIGURE 5. Minute conulariid specimen. (A) Conulariid specimen of Archaeoconularia fecunda and trepostome bryozoan colony; coated with ammonium chloride, no. NMP L21990, locality Loděnice, Upper Ordovician, Zahořany Formation (lower Katian) (B) Micro-CT visualizing of inner surfaces. Scale bar equals 5 mm.

FIGURE 3 in Benefits and limits of x-ray micro-computed tomography for visualization of colonization and bioerosion of shelled organisms

FIGURE 3. Siliceous nodules of the Šárka Formation. (A, B) Pricyclopyge binodosa, complete trilobite, no. NMP L 35055, locality Praha-Šárka, Middle Ordovician (Darriwilian), (A) Enrolled trilobite coated with ammonium chloride, exterior of objects. (B) Micro-CT image showing dense burrows, interior of objects. (C, D) Rostrum with eyes of a trilobite P. binodosa, no. NMP L46892, locality Praha-Šárka, Middle Ordovician (Darriwilian). (C) Rostrum coated with ammonium chloride, exterior of objects. (D) Micro-CT visualization of tunnels, interior of objects. (E) Bivalve Redonia deshayesi, micro-CT image showing trace fossils, interior of objects, no. NMP L 51722, locality Osek, Middle Ordovician (Darriwilian). All scale bars equal 5 mm.

FIGURE 2 in Benefits and limits of x-ray micro-computed tomography for visualization of colonization and bioerosion of shelled organisms

FIGURE 2. Custom-made holders specially adapted for each scanned specimen. (A) Plastic cup. (B) Polystyrene holder. (C) Aluminum holder for small specimens. (D) Plastic tube filled with polystyrene.

FIGURE 1 in Benefits and limits of x-ray micro-computed tomography for visualization of colonization and bioerosion of shelled organisms

FIGURE 1. (A) Single x-ray projection. Schematic representation of positioning of the investigated object inside x-ray device. (B) Multiple x-ray projections as the object rotates. Positioning of investigated object inside micro-CT device. (C) Example of 3D dataset, i.e., a group of 2D slice images acquired by the MicroCT scanner. (D) Examples of Volume rendering; technique in visualization and computer graphics, used to display object from 3D data set in different aspects and orientations.

FIGURE 6 in Benefits and limits of x-ray micro-computed tomography for visualization of colonization and bioerosion of shelled organisms

FIGURE 6. Tube fragments of the serpulid polychaete Pyrgopolon (Pyrgopolon) deforme. Left images show exterior of objects; right images show interior of objects. (A) Specimen encrusted with bryozoan colonies and serpulid worms, boreholes assigned to Entobia Bronn, 1837, representing the most common ichnogenus in the examined serpulid tubes, no. MHNLM EMV 2016.3.14. (B) Intensely bored specimen preserving tunnels of ichnogenera Entobia and Trypanites Mägdefrau, 1932, no. MHNLM EMV 2016.3.44. (C) Serpulid tube with Entobia boreholes and encrusting juvenile oyster, no. MHNLM EMV 2016.3.40. Scale bar equals 1 cm.

opencc-by-4.0Mar 2022View details →

Trajectory with Overlapping Projections x-ray Computed Tomography (TOP-CT) dataset of 23 mandarins moving over a circular trajectory

SummaryThis dataset is a collection of X-ray projection images of 23 mandarins moving over a circular trajectory in such a way that the projections of multiple adjacent mandarins overlap. The dataset was acquired to test out Trajectory with Overlapping Projections x-ray Computed Tomography (TOP-CT), about which a paper is published in IEEE Transactions on Computational Imaging [Schut 2022]. DescriptionSample informationThe samples are 23 mandarins. The first 10 are of the Nadorcott cultivar, and the remaining 13 are of the Clemenrubi cultivar. The diameter of the mandarins ranges between 50 and 58 mm. Per sample metadata can be found in the mandarin_metadata.csv file.Scanner informationThe dataset is acquired in the FleX-ray Laboratory, developed by TESCAN-XRE, located at CWI in Amsterdam. The CT scanner consists consists of a cone-beam microfocus polychromatic X-ray point source, and a 1944x1536 pixel, 14-bit, flat detector panel (Dexela1512NDT). Full details can be found in [Coban 2020].Scanning geometryThe mandarins were moved according to a custom scanning protocol, with the intention to simulate a conveyor belt setup. A wooden disk was attached on top of the rotation stage and six evenly spaced object positions were marked on the disk at a fixed distance from the center of rotation. Pieces of cardboard tube were used as sample holders to make sure the mandarins wouldn't roll as the disk would rotate and to raise them from the disk without attenuating too much of the X-ray signal. The rotation stage was positioned in such a way that over a full rotation of the disk, each mandarin would be completely in view of the detector for more than 180 degrees of the rotation, while there would also be a position at which it would be completely out of view. An image illustrating the exact dimensions is included in mandarin_carousel_dimensions.png.The scan was performed in phases. Every phase 400 projection images were acquired, while rotating the disk for 60 degrees. This would rotate one of the positions out of view of the scanning setup. Before the first 6 phases a mandarin was added on the position that was out of view of the setup. For the phases after that the position that would be out of view would contain a mandarin that had rotated the full circle so that mandarin was replaced with a new mandarin. At the last 6 phases there would be no new mandarins left to add so the mandarin that was out of view of the setup would only be removed. The projection images acquired from each phase were concatenated resulting in a dataset of 11200 projections. At most 5 mandarins were in view at a given time.Note: Due to a small oversight while scanning, the 19th mandarin is not included on projections 9200-9205. This area can be masked out during reconstruction.Scanning settingsA peak voltage of 90kV was used, the target power was set to 49.5W and the spectrum was pre-filtered using 0.1mm of copper. An exposure time of 200 ms was used for each projection. A start-stop acquisition scheme was used to minimize vibrations and to make adding and removing mandarins easier: After each projection image was acquired, the stage was rotated to a new position and the scanner was paused for 200 ms before acquiring the next projection image. Darkfield and flatfield images were acquired before and after all the mandarins were scanned using the average over 200 images. 2x2 pixel hardware binning was used and all images were cropped to a 500 pixel high region around the center, resulting in 11200 projection images of 956x500 pixels (11.1GB uncompressed). All images are stored in .tif format.Reconstructing volumesThe repository <a href="https://github.com/D1rk123/top-ct_experiments">https://github.com/D1rk123/top-ct_experiments</a> contains code for TOP-CT simulations and reconstructions. The script mandarin_carousel_experiment.py was specifically written to reconstruct volumes for each separate mandarin from this dataset. Research group These datasets are produced by the Computational Imaging group at Centrum Wiskunde & Informatica (CI-CWI) in Amsterdam, The Netherlands: <a href="https://www.cwi.nl/research/groups/computational-imaging">https://www.cwi.nl/research/groups/computational-imaging</a>Contact details dirk [dot] schut [at] cwi [dot] nlAcknowledgments This work was funded by the Dutch Research Council (NWO) through the UTOPIA project (ENWSS.2018.003). The authors also acknowledge TESCAN-XRE NV for their collaboration and support of the FleX-ray laboratory.References[Schut 2022] D. E. Schut, K. J. Batenburg, R. van Liere, and T. van Leeuwen, "TOP-CT: Trajectory with Overlapping Projections X-ray Computed Tomography", 2022, IEEE Transactions on Computational Imaging [Coban 2020] S. B. Coban, F. Lucka, W. J. Palenstijn, D. Van Loo, and K. J. Batenburg, "Explorative imaging and its implementation at the FleX-ray Laboratory," J. Imaging, vol. 6, no. 18, 2020, doi: 10.3390/jimaging6040018.If you use (parts of) this data in a publication, please consider citing the first article.

opencc-by-4.0Sep 2022View details →

X-ray computed tomography dataset of a walnut

walnut_scan: <ul> <li>scan performed with a conventional micro-CT</li> <li>1601 acquired projections as tiff stack</li> <li>info file containing corresponding metadata</li> </ul>   walnut_rec: <ul> <li>reconstructed volume as tiff stack</li> <li>info file containing corresponding metadata</li> <li>reconstruction performed with pyXIT (see reference)</li> </ul>

opencc-by-4.0May 2024View details →

Multienergy Fan Beam Computed Tomography Dataset of a Bird Chest Imaged with 3 Different X-ray Spectra

Summary This dataset is a collection of X-ray projection data of a biological imaging phantom (a bird chest) imaged in an X-ray microtomography scanner, using three different X-ray spectra. The dataset also includes a metadata file for each of the scans, specifying the scan geometry and other important scan parameters, as well as photographs and example reconstructions. The dataset is designed for use in algorithm development for multienergy computed tomography.   Description Sample Information The sample is the chest of a common quail (Coturnix coturnix) bird obtained frozen from a local supermarket. The chest section of the frozen bird was removed using a handsaw, and left to melt and settle in a sample holder before imaging. Scanner The measurement data were acquired using an X-ray microtomography scanner in the University of Helsinki Micro-CT Laboratory. The scanner uses cone beam geometry and it is equipped with an end-window tube with a tungsten target. Scan Settings The dataset consists of three consecutive scans made using identical geometry but different X-ray spectra and detector exposure times. For each scan, 720 X-ray projections were acquired using an angle increment of 0.5 degrees. Multiple frames were averaged for each projection in order to increase signal-to-noise ratio. The scan geometry and the energy-specific settings are summarized in the following two tables. Table 1. Imaging geometry used for collecting the data. <table> <tbody> <tr> <td>Parameter</td> <td>Value</td> </tr> <tr> <td>Focus-center distance</td> <td>252 mm</td> </tr> <tr> <td>Focus-detector distance</td> <td>420 mm</td> </tr> <tr> <td>Geometric magnification</td> <td>5/2</td> </tr> <tr> <td>Detector pixel size</td> <td>0.200 mm</td> </tr> <tr> <td>Effective pixel size</td> <td>0.120 mm</td> </tr> <tr> <td>Projection size</td> <td>552 x 576 pixels</td> </tr> <tr> <td>Angular range</td> <td>360'</td> </tr> <tr> <td>#projections</td> <td>720</td> </tr> </tbody> </table> Table 2. Energy-specific settings used for collecting the data. <table> <tbody> <tr> <td>Energy label</td> <td>U (kV)</td> <td>Filtration</td> <td>I (μA)</td> <td>Exposure time (ms)</td> <td>Frame averaging</td> </tr> <tr> <td>E1</td> <td>50</td> <td>None</td> <td>300</td> <td>125</td> <td>4</td> </tr> <tr> <td>E2</td> <td>80</td> <td>1 mm Al</td> <td>180</td> <td>125</td> <td>4</td> </tr> <tr> <td>E3</td> <td>120</td> <td>0.5 mm Cu</td> <td>120</td> <td>250</td> <td>4</td> </tr> </tbody> </table> Data Post-Processing Before the scans were made, a dark current image and flat-field image were acquired for each scan setting. During the scans, dark current subtraction and flat-field correction were automatically applied to the X-ray projections by the measurement software. Data Contents This dataset contains the following files: <ul> <li>The raw projection data (.tif format) for each scan and a metadata file (.txt format) describing the measurement setup, with formatting that is both human-readable and machine-readable.</li> <li>Pre-created 2D sinograms for each energy level. The sinograms have been created from the central plane of the cone beam, which reduces to fan beam geometry. The sinograms are stored in Matlab's .mat file format in data structures which also contain metadata on the measurement.</li> <li>Photographs taken during the measurement process.</li> <li>Example filtered backprojection (FBP) reconstructions of the central plane of the phantom for each energy. The reconstructions were computed using the  Phoenix datos|x CT software provided with the microtomography scanner</li> </ul>   Research Group This dataset was produced by the Inverse Problems research group at the Department of Mathematics and Statistics at the University of Helsinki, Finland (<a href="https://www.helsinki.fi/en/researchgroups/inverse-problems">https://www.helsinki.fi/en/researchgroups/inverse-problems</a>) in collaboration with the Computational Physics and Inverse Problems research group at the University of Eastern Finland, Finland (<a href="https://sites.uef.fi/inverse">https://sites.uef.fi/inverse</a>) and the X-ray Laboratory at the Department of Physics at the University of Helsinki, Finland (<a href="https://www.helsinki.fi/en/researchgroups/x-ray-laboratory">https://www.helsinki.fi/en/researchgroups/x-ray-laboratory</a>).   Previous Use This dataset has been used in the following publications: Jussi Toivanen, Alexander Meaney, Samuli Siltanen, Ville Kolehmainen. Joint reconstruction in low dose multi-energy CT. Inverse Problems and Imaging, 2020, 14(4): 607-629. doi: <a href="https://doi.org/10.3934/ipi.2020028" target="_blank" rel="noopener">10.3934/ipi.2020028</a>. E. Cueva, A. Meaney, S. Siltanen, M. J. Ehrhardt. Synergistic multi-spectral CT reconstruction with directional total variation. Philos Trans A Math Phys Eng Sci. 2021 Aug 23;379(2204):20200198. doi: <a href="https://doi.org/10.1098/rsta.2020.0198">10.1098/rsta.2020.0198</a>.   Additional Links To get started with the data, we recommend looking at the HelTomo toolbox, specifically created for working with CBCT data collected by the Inverse Problems research group, and available at <a href="https://se.mathworks.com/matlabcentral/fileexchange/74417-heltomo-helsinki-tomography-toolbox">https://se.mathworks.com/matlabcentral/fileexchange/74417-heltomo-helsinki-tomography-toolbox</a>.   Acknowledgements We wish to thank laboratory engineer Heikki Suhonen for his guidance and assistance in conducting the measurements.   Contact Details For more information or guidance in using these datasets, please contact alexander.meaney [at] helsinki.fi.

Figure 1 in The first extinct species of Acritus LeConte, 1853 (Histeridae: Abraeinae) from Eocene Baltic amber: a microscopic beetle inclusion studied with X-ray micro-computed tomography

Figure 1. Photomicrographs of Acritus sutirca sp. nov., holotype, no. 5541 (MAIG), habitus: (a) ventral view; (b) dorsal view; (c) left lateral view; (d) frontal view. Scale bar represents 0.2 mm.

Figure 2. X in The first extinct species of Acritus LeConte, 1853 (Histeridae: Abraeinae) from Eocene Baltic amber: a microscopic beetle inclusion studied with X-ray micro-computed tomography

Figure 2. X-ray micro-CT renderings of Acritus sutirca sp. nov., holotype, no. 5541 (MAIG), habitus: (a) dorsal view; (b) left lateral view; (c) ventral view; (d) right lateral view. Scale bar represents 0.2 mm.

Figure 4. X in The first extinct species of Acritus LeConte, 1853 (Histeridae: Abraeinae) from Eocene Baltic amber: a microscopic beetle inclusion studied with X-ray micro-computed tomography

Figure 4. X-ray micro-CT renderings of Acritus sutirca sp. nov., holotype, no. 5541 (MAIG): (a–d) aedeagus in dorsal, ventral view and lateral views; (e) antennae. Scale bar represents 0.1 mm.

Figure 3. X in The first extinct species of Acritus LeConte, 1853 (Histeridae: Abraeinae) from Eocene Baltic amber: a microscopic beetle inclusion studied with X-ray micro-computed tomography

Figure 3. X-ray micro-CT renderings of Acritus sutirca sp. nov., holotype, no. 5541 (MAIG), habitus: (a) frontal view; (b) caudal view. Scale bar represents 0.2 mm. Abbreviations: a1 – antennomere 1 (scape); ey – compound eye; py – pygidium; pp – propygidium.

FIGURE 2 in Non-destructive analysis of in situ ammonoid jaws by synchrotron radiation X-ray micro-computed tomography

FIGURE 2. Reconstructed tomographic images of the specimen (1) and its internal structure in median section (2). The lower and upper jaws are enlarged in (3) and (4), respectively.

FIGURE 5 in Non-destructive analysis of in situ ammonoid jaws by synchrotron radiation X-ray micro-computed tomography

FIGURE 5. Three-dimensional reconstruction of the upper and lower jaws preserved in the body chamber of the specimen. The reconstructed parts are inside the specimen (1). The jaws are preserved close to each other (2).

FIGURE 1 in Non-destructive analysis of in situ ammonoid jaws by synchrotron radiation X-ray micro-computed tomography

FIGURE 1. Left lateral (1), dorsal (2) and ventral (3) views of Phyllopachyceras ezoensis with preserved upper and lower jaws in situ within the body chamber. UMUT MM 27831 (modified from Tanabe et al., 2013).

FIGURE 7 in Non-destructive analysis of in situ ammonoid jaws by synchrotron radiation X-ray micro-computed tomography

FIGURE 7. Result of segmentation of the upper jaw of the specimen, from frontal (1), rear (2), left-lateral (3) views and the transverse section of the area (4) indicated as a square in (3). The three-dimensional reconstruction (5) shows areal distributions of the "chitinous" lamellae and the calcareous covering. The reconstruction of the transverse section (6), which corresponds to (4), shows the architecture of the outer lamella. The abbreviations are indicated in (5).