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36 results for “XCT”
XCT data of metallic feedstock powder with pore size analysis
<p><strong>X-Ray computed tomography (XCT) scan of 11 individual metallic powder particles, made of (Mn,Fe)<sub>2</sub>(P,Si) alloy</strong></p> <p>The data set consists of 4 single XCT scans which have been stitched together [3] after reconstruction.<br> The powder material is an (Mn,Fe)<sub>2</sub>(P,Si) alloy with an average density of 6.4 g/cm³. The particle size range is about 100 - 150 µm with equivalent pore diameters up to 75 µm. The powder and the metallic alloy are described in detail in [1, 2].</p> <p><strong>Data acquisition</strong></p> <p>The data was acquired using a Zeiss Xradia 620 Versa X-ray microscope which provides the opportunity of optical magnification.</p> <table> <caption><strong>Tomographic imaging parameters</strong></caption> <tbody> <tr> <td>XCT system</td> <td>Zeiss Xradia 620 Versa</td> </tr> <tr> <td>Voltage</td> <td>80</td> <td>kV</td> </tr> <tr> <td>Power</td> <td>10</td> <td>W</td> </tr> <tr> <td>Source filtering</td> <td>"<em>LE2</em>" (system specific)</td> <td>-</td> </tr> <tr> <td>Source-object distance</td> <td>10</td> <td>mm</td> </tr> <tr> <td>Object-detector distance</td> <td>10</td> <td>mm</td> </tr> <tr> <td>Geom. magnification</td> <td>2</td> <td>-</td> </tr> <tr> <td>Optical magnification</td> <td>20</td> <td>-</td> </tr> <tr> <td>Native pixel size</td> <td>13.5</td> <td>µm</td> </tr> <tr> <td>Binning</td> <td>2x2</td> <td>px</td> </tr> <tr> <td>Voxel size</td> <td>0.68</td> <td>µm</td> </tr> <tr> <td>No. of projections per scan</td> <td>801</td> <td>1</td> </tr> <tr> <td>No. of scans</td> <td>4</td> <td>-</td> </tr> <tr> <td>Exposure time per projection</td> <td>5</td> <td>s</td> </tr> </tbody> </table> <p> </p> <p><strong>Projection data</strong> (801 single TIFF-files each):</p> <ul> <li>proj_00</li> <li>proj_01</li> <li>proj_02</li> <li>proj_03</li> </ul> <p><strong>Reconstructed data</strong>:</p> <ul> <li>raw-volume (MnFePSi-Powder_80kV_10W_LE2_20x_5s_801_0p68_BHC=2_Stitch_U16_966x1020x2916.raw + header.txt)</li> <li>analyzed data as Volume Graphics Studio MAX 3.4.5 project</li> </ul> <p><strong>Stitched 2D data</strong> (images stitched with ImageJ-Plugin described in [3]<strong>:</strong></p> <ul> <li>Stitched_0deg_Projections.tif</li> <li>Pores+Particles_Analysis.tif</li> </ul> <p> </p> <p>[1] G.-R. Jaenisch, U. Ewert, A. Waske, and A. Funk, “Radiographic Visibility Limit of Pores in Metal Powder for Additive Manufacturing,” Metals, vol. 10, no. 12, p. 1634, Dec. 2020. https://doi.org/10.3390/met10121634</p> <p>[2] X. Miao et al., “Printing (Mn,Fe)2(P,Si) magnetocaloric alloys for magnetic refrigeration applications,” J. Mater. Sci., vol. 55, no. 15, pp. 6660–6668, May 2020. https://doi.org/10.1007/s10853-020-04488-8</p> <p>[3] S. Preibisch, S. Saalfeld, and P. Tomancak, “Globally optimal stitching of tiled 3D microscopic image acquisitions,” Bioinformatics, vol. 25, no. 11, pp. 1463–1465, Jun. 2009.</p>
Cross-sectional images from x-ray computed tomography (XCT) of conserved archaeological samples
<p>The repository contains cross-sections of 83 wood samples derived from X-ray computed tomography (CT) data. The samples are a part of the LEIZA reference collection, which were created within the framework of the project "Mass Finds in Archaeological Collections", which was funded by the "Kulturstiftung des Bundes" and the "Kulturstiftung der Länder" from 15.04.2008 to 31.12.2011 as part of the "Program for the Conservation and Restoration of Mobile Cultural Property" (KUR, see www.rgzm.de/kur).</p> <p>Around 10 years later, during the CuTAWAY project (ConservaTion And Wod AnalYses), the wood samples were digitized using an in-house laboratory X-ray CT system (Diondo d2, Germany) at HSLU with a nominal voxel size between 27 and 44 μm in order to analyse the structure of the interior. You can download the cross-sectional images of the data here. The 3D data acquisition was carried out during November 2019 - April 2021.</p> <p>The CuTAWAY project was funded by the German Research Association (DFG) and the Swiss National Science Foundation (SNSF) from 2019 to 2023 (CuTAWAY - Conservation and Wood Analyses, DFG - 416877131 and SNSF - 200021E_183684).</p>
Fig. 4 in Applications and limitations of micro-XCT imaging in the studies of Permian radiolarians: A new genus with bi-polar main spines
Fig. 4. Dendrogram of the cluster analysis under the corresponding analysis based on nine genera (performed by software "R" and the EZR).
Fig. 3 in Applications and limitations of micro-XCT imaging in the studies of Permian radiolarians: A new genus with bi-polar main spines
Fig. 3. Schematic drawings on internal structure of Permian and Mesozoic spumellarians with bi-polar main spines (detailed information including source is summarized in Table 2). A, B. Protopsium. C. Pegoxystris. D. Falcispongus. E. Spongoxystris. F. Dalongicaepa Xiao and Suzuki gen. nov. G. Spongotortilispinus. H. Spongopallium. I, J. Archaeospongoprunum. K. Palaeospongurus. L. Paroertlispongus.
Fig. 2 in Applications and limitations of micro-XCT imaging in the studies of Permian radiolarians: A new genus with bi-polar main spines
Fig. 2. Micro-XCT cross-sectional images (A, B), SEM micrographs (C–E), and TLM micrographs (F) of the spumellarian Tetraspongodiscus stauracanthus Feng in Feng et al., 2006 from Changhsingian of the Rencunping section (A–D) and Dongpan (E), South China and upper Capitanian of West Texas, USA (F). A. LGFEC SR 33-201. B. LGFEC SR 33-202. C. LGFEC SR 36-011. D. LGFEC SR 33-022. E. DP 4/4860 (from Feng et al. 2006; copyright is permitted from Elsevier). F. S3-2A (from Noble and Jin 2010). Different cross sections show clear hoops with few primary beams and a possible median bar (A1 and B1), the centrical internal spicule (A2), and the embedded proximal part of the main spines (B2). Scale bars 50 μm.
Micro-XCT chondrule classification for subsequent isotope analys
<p>Datasets of chondrule samples analyzed for publication " Micro-XCT chondrule classification for subsequent isotope analysis" in Meteoritics & Planetary Science <a href="http://dx.doi.org/10.1111/maps.14026">http://dx.doi.org/10.1111/maps.14026</a></p>
XCT scanning results of CFRPs
<p>High resolution images of chapter 5 of the PhD thesis from Evelien Zwanenburg</p>
Simulated Shapes for ORMIR_XCT Thickness Measurement Validation
<p>These shapes were generated to validate a distance transform function implemented for the <a href="https://github.com/SpectraCollab/ORMIR_XCT">Python ORMIR_XCT package</a>. Shapes generated include: solid spheres, solid cylinders, hollow spheres, hollow cylinders, and plates. All shapes have a voxel size of 1 mm^3. Image naming convention is as follows:</p> <ol> <li><strong>Solid (filled) Spheres: </strong>F_SPH_OUTR_X.nii <ul> <li>Radius of the sphere = X</li> </ul> </li> <li><strong>Solid (filled) Cylinders:</strong> F_CYL_OUTR_X_LEN_Y.nii <ul> <li>Radius of the cylinder = X</li> <li>Length of the cylinder = Y</li> </ul> </li> <li><strong>Hollow Spheres:</strong> H_SPH_OUTR_X_INR_Y.nii <ul> <li>Outer radius of the sphere = X</li> <li>Inner radius of the sphere = Y</li> </ul> </li> <li><strong>Hollow Cylinders: </strong>H_CYL_OUTR_X_INR_Y_LEN_Z.nii <ul> <li>Outer radius of the cylinder = X</li> <li>Inner radius of the cylinder = Y</li> <li>Length of the cylinder = Z</li> </ul> </li> <li><strong>Plates:</strong> PLATE_WIDTH_X_LEN_Y.nii <ul> <li>Width (i.e., thickness) of the plate = X</li> <li>Length of the plate = Y (plates are all squares)</li> </ul> </li> </ol>
XCT dataset for the Fiji tutorial
<p>A sample XCT dataset for the Fiji tutorial.</p>
PsA Secukinumab XCT Structural Progression Study
ClinicalTrials.gov study NCT03623867. IPD Sharing: UNDECIDED. Countries: 1. Publications: 20.
Overview of XCT data processing workflow for ammonium nitrate prills quantitative analysis
<p>This video presents the data processing workflow that was developped to perform the quantitative structureal and morphological analysis of ammonium nitrate prills by X-ray computed tomography.. </p>
ATF4 suppresses hepatocarcinogenesis by inducing SLC7A11 (xCT) to suppress stress-related ferroptosis
GEO Series GSE191115. Mus musculus. 12 samples. Type: Expression profiling by high throughput sequencing.
Genomic analysis of xCT-mediated regulatory network: identification of novel targets against AIDS-associated lymphoma
GEO Series GSE65418. Homo sapiens. 12 samples. Type: Expression profiling by array.
XCT is a novel regulator of chromatin functionally conserved across eukaryotes
GEO Series GSE67813. Arabidopsis thaliana. 18 samples. Type: Expression profiling by high throughput sequencing; Methylation profiling by high throughput sequencing.
Glutamine sensitivity analysis identifies the xCT antiporter as a common triple negative breast tumor therapeutic target.
GEO Series GSE48984. Homo sapiens. 26 samples. Type: Expression profiling by array.
Inhibition of xCT Suppresses Melanoma progress
GEO Series GSE166566. Mus musculus. 6 samples. Type: Expression profiling by high throughput sequencing.
Patient-Specific Pharmacogenomics demonstrates xCT as Predictive Therapeutic Target in Colon Cancer with Possible Implications in Tumor Connectivity
GEO Series GSE305337. Homo sapiens. 73 samples. Type: Expression profiling by high throughput sequencing.
IBSim Virtual Test Benchmark Data - Experiment Type: Thermal (LFA), SampleID: LFA_RNA_A01, Data: XCT
<p>Sample ID: LFA_RNA_A01</p> <p>X-ray tomography (CT) image data of a Ti6Al4V disc. The 3D image was generated with an X-ray tomography scan performed by Dr Llion Evans with Swansea University, Advanced Imaging of Materials (AIM) equipment.</p> <p>The dataset includes: raw radiographs; scan & reconstruction parameter settings file; reconstructed 3D volume. To visualise the 3D volume use software such as ImageJ (https://imagej.net/Fiji/Downloads). The volume image data (.raw file) is in binary format and has the following characteristics: 1920 x 1920 x 1536; 16-bit; little-endian byte order.</p> <p>This data is part of a 'virtual testing' benchmark study, where samples are tested physically in the lab and their microscale accurate digital equivalent are tested virtually through simulation. The technique of converting 3D volumetric images directly into finite element method (FEM) meshes is part of the Image-Based Simulation (IBSim) approach.</p> <p>This data is part of a batch of samples for thermal testing via laser flash analysis (LFA), following the standards ASTM E1461 / ASTM E2585. As part of the study, controlled defects were introduced into the samples. This was achieved by machining a disc shaped recess (of defined diameter and depth) into one disc which is bonded onto another disc, so that the defect is located internally within the final sample.</p> <p>The samples in the batch are named as follows.</p> <p>Sample ID Diameter Thickness Recess d Recess t<br> LFA_RNA_### 12.6 2.5 N/A N/A<br> LFA_Rd0t00_### 12.6 1.25 x 2 N/A N/A<br> LFA_Rd8t02_### 12.6 1.25 x 2 8.0 0.2<br> LFA_Rd8t08_### 12.6 1.25 x 2 8.0 0.8<br> LFA_Rd6t02_### 12.6 1.25 x 2 6.0 0.2<br> LFA_Rd6t08_### 12.6 1.25 x 2 6.0 0.8<br> LFA_Rd4t02_### 12.6 1.25 x 2 4.0 0.2<br> LFA_Rd4t08_### 12.6 1.25 x 2 4.0 0.8</p> <p>Where ### denotes the furnace bonding batch (A-C and N for no bonding cycle) and sample number (01-30). Values in mm.</p> <p> </p>
IBSim Virtual Test Benchmark Data - Experiment Type: Thermal (LFA), SampleID: LFA_Rd0t00_A20, Data: XCT
<p>Sample ID: LFA_Rd0t00_A20</p> <p>X-ray tomography (CT) image data of a Ti6Al4V disc. The 3D image was generated with an X-ray tomography scan performed by Dr Llion Evans with Swansea University, Advanced Imaging of Materials (AIM) equipment.</p> <p>The dataset includes: raw radiographs; scan & reconstruction parameter settings file; reconstructed 3D volume. To visualise the 3D volume use software such as ImageJ (https://imagej.net/Fiji/Downloads). The volume image data (.raw file) is in binary format and has the following characteristics: 1920 x 1920 x 1536; 16-bit; little-endian byte order.</p> <p>This data is part of a 'virtual testing' benchmark study, where samples are tested physically in the lab and their microscale accurate digital equivalent are tested virtually through simulation. The technique of converting 3D volumetric images directly into finite element method (FEM) meshes is part of the Image-Based Simulation (IBSim) approach.</p> <p>This data is part of a batch of samples for thermal testing via laser flash analysis (LFA), following the standards ASTM E1461 / ASTM E2585. As part of the study, controlled defects were introduced into the samples. This was achieved by machining a disc shaped recess (of defined diameter and depth) into one disc which is bonded onto another disc, so that the defect is located internally within the final sample.</p> <p>The samples in the batch are named as follows.</p> <p>Sample ID Diameter Thickness Recess d Recess t<br> LFA_RNA_### 12.6 2.5 N/A N/A<br> LFA_Rd0t00_### 12.6 1.25 x 2 N/A N/A<br> LFA_Rd8t02_### 12.6 1.25 x 2 8.0 0.2<br> LFA_Rd8t08_### 12.6 1.25 x 2 8.0 0.8<br> LFA_Rd6t02_### 12.6 1.25 x 2 6.0 0.2<br> LFA_Rd6t08_### 12.6 1.25 x 2 6.0 0.8<br> LFA_Rd4t02_### 12.6 1.25 x 2 4.0 0.2<br> LFA_Rd4t08_### 12.6 1.25 x 2 4.0 0.8</p> <p>Where ### denotes the furnace bonding batch (A-C and N for no bonding cycle) and sample number (01-30). Values in mm.</p>
IBSim Virtual Test Benchmark Data - Experiment Type: Thermal (LFA), SampleID: LFA_Rd4t08_A15, Data: XCT
<p>Sample ID: LFA_Rd4t08_A15</p> <p>X-ray tomography (CT) image data of a Ti6Al4V disc. The 3D image was generated with an X-ray tomography scan performed by Dr Llion Evans with Swansea University, Advanced Imaging of Materials (AIM) equipment.</p> <p>The dataset includes: raw radiographs; scan & reconstruction parameter settings file; reconstructed 3D volume. To visualise the 3D volume use software such as ImageJ (https://imagej.net/Fiji/Downloads). The volume image data (.raw file) is in binary format and has the following characteristics: 1920 x 1920 x 1536; 16-bit; little-endian byte order.</p> <p>This data is part of a 'virtual testing' benchmark study, where samples are tested physically in the lab and their microscale accurate digital equivalent are tested virtually through simulation. The technique of converting 3D volumetric images directly into finite element method (FEM) meshes is part of the Image-Based Simulation (IBSim) approach.</p> <p>This data is part of a batch of samples for thermal testing via laser flash analysis (LFA), following the standards ASTM E1461 / ASTM E2585. As part of the study, controlled defects were introduced into the samples. This was achieved by machining a disc shaped recess (of defined diameter and depth) into one disc which is bonded onto another disc, so that the defect is located internally within the final sample.</p> <p>The samples in the batch are named as follows.</p> <p>Sample ID Diameter Thickness Recess d Recess t<br> LFA_RNA_### 12.6 2.5 N/A N/A<br> LFA_Rd0t00_### 12.6 1.25 x 2 N/A N/A<br> LFA_Rd8t02_### 12.6 1.25 x 2 8.0 0.2<br> LFA_Rd8t08_### 12.6 1.25 x 2 8.0 0.8<br> LFA_Rd6t02_### 12.6 1.25 x 2 6.0 0.2<br> LFA_Rd6t08_### 12.6 1.25 x 2 6.0 0.8<br> LFA_Rd4t02_### 12.6 1.25 x 2 4.0 0.2<br> LFA_Rd4t08_### 12.6 1.25 x 2 4.0 0.8</p> <p>Where ### denotes the furnace bonding batch (A-C and N for no bonding cycle) and sample number (01-30). Values in mm.</p>
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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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.