Find research datasets worth reusing

opencc-by-4.0Jul 2024View details →

Cross-sectional images from x-ray computed tomography (XCT) of conserved archaeological samples

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). 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. 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).

Zinc Doped Zeolite 13X DIAD X-Ray Computed Tomography - 0.54 micron pixel size RAW

This repository contains raw data for the zinc-doped zeolite 13X sample imaged on the DIAD beamline at Diamond Light Source. Data is stored as a .nxs file which can be loaded using ImageJ/Fiji. The size of this dataset is 2510x2510x2110 with a pixel-size of 0.54 microns. A script containing the savu process list and code used to perform the 3D reconstruction is provided. A detailed data descriptor pre-print can be found at https://arxiv.org/abs/2409.07322#   The size of the .h5 file is >50GB and cannot be downloaded from the browser. It is recommended to use a terminal to download the data using the 'curl' or 'wget' command. To generate a file url, right-click the 'Download' button for the dataset you want to download and select 'Copy Link. Enter the following command in your terminal to download the dataset: <blockquote> curl dataset_url > 43334_raw.h5 </blockquote> Please replace dataset_url with the url you copied.

Zinc Doped Zeolite 13X I13-2 X-Ray Computed Tomography - 1.625 micron pixel size

This repository contains data for the zinc-doped zeolite 13X sample imaged on the I13-2 beamline at Diamond Light Source. Data is stored as a .h5 file which can be loaded using ImageJ/Fiji. The size of this dataset is 2510x2510x2110 with a pixel-size of 1.625 microns. This data is one of four resolutions obtained. A detailed data descriptor pre-print is available at https://arxiv.org/abs/2409.07322# The size of the .h5 file is >50GB and cannot be downloaded from the browser. It is recommended to use a terminal to download the data using the 'curl' or 'wget' command. To generate a file url, right-click the 'Download' button for the dataset you want to download and select 'Copy Link. Enter the following command in your terminal to download the dataset: <blockquote> curl dataset_url > 169067_recon.h5 </blockquote> Please replace dataset_url with the url you copied.

Zinc Doped Zeolite 13X DIAD X-Ray Computed Tomography - 0.54 micron pixel size

This repository contains processed data for the zinc-doped zeolite 13X sample imaged on the DIAD beamline at Diamond Light Source. Data is stored as a .nxs file which can be loaded using ImageJ/Fiji. The size of this dataset is 2510x2510x2110 with a pixel-size of 0.54 microns. A script containing the savu process list and code used to perform the 3D reconstruction is provided. A detailed data descriptor pre-print is available at https://arxiv.org/abs/2409.07322# The size of the .h5 file is >50GB and cannot be downloaded from the browser. It is recommended to use a terminal to download the data using the 'curl' or 'wget' command. To generate a file url, right-click the 'Download' button for the dataset you want to download and select 'Copy Link. Enter the following command in your terminal to download the dataset: <blockquote> curl dataset_url > 43334_recon.h5 </blockquote> Please replace dataset_url with the url you copied.

Zinc Doped Zeolite 13X I13-2 X-Ray Computed Tomography - 0.325 micron pixel size

This repository contains data for the zinc-doped zeolite 13X sample imaged on the I13-2 beamline at Diamond Light Source. Data is stored as a .h5 file which can be loaded using ImageJ/Fiji. The size of this dataset is 2510x2510x2110 with a pixel-size of 0.325 microns. This data is one of four resolutions obtained. A detailed data descriptor pre-print is available at https://arxiv.org/abs/2409.07322# The size of the .h5 file is >50GB and cannot be downloaded from the browser. It is recommended to use a terminal to download the data using the 'curl' or 'wget' command. To generate a file url, right-click the 'Download' button for the dataset you want to download and select 'Copy Link. Enter the following command in your terminal to download the dataset: <blockquote> curl dataset_url > 169065_recon.h5 </blockquote> Please replace dataset_url with the url you copied.

Zinc Doped Zeolite 13X I13-2 X-Ray Computed Tomography - 0.8125 micron pixel size

This repository contains data for the zinc-doped zeolite 13X sample imaged on the I13-2 beamline at Diamond Light Source. Data is stored as a .h5 file which can be loaded using ImageJ/Fiji. The size of this dataset is 2510x2510x2110 with a pixel-size of 0.8125 microns. This data is one of four resolutions obtained. A detailed data descriptor pre-print is available at https://arxiv.org/abs/2409.07322# The size of the .h5 file is >50GB and cannot be downloaded from the browser. It is recommended to use a terminal to download the data using the 'curl' or 'wget' command. To generate a file url, right-click the 'Download' button for the dataset you want to download and select 'Copy Link. Enter the following command in your terminal to download the dataset: <blockquote> curl dataset_url > 169066_recon.h5 </blockquote> Please replace dataset_url with the url you copied.

Zinc Doped Zeolite 13X I13-2 X-Ray Computed Tomography - 2.6 micron pixel size

This repository contains data for the zinc-doped zeolite 13X sample imaged on the I13-2 beamline at Diamond Light Source. Data is stored as a .h5 file which can be loaded using ImageJ/Fiji. The size of this dataset is 2510x2510x2110 with a pixel-size of 2.6 microns. This data is one of four resolutions obtained. A detailed data descriptor pre-print is available at https://arxiv.org/abs/2409.07322# The size of the .h5 file is >50GB and cannot be downloaded from the browser. It is recommended to use a terminal to download the data using the 'curl' or 'wget' command. To generate a file url, right-click the 'Download' button for the dataset you want to download and select 'Copy Link. Enter the following command in your terminal to download the dataset: <blockquote> curl dataset_url > 169068_recon.h5 </blockquote> Please replace dataset_url with the url you copied.

opencc-by-4.0Nov 2023View details →

Synchrotron X-ray Computed Tomography scan of a wasp

<h4>Contents:</h4><ul><li>bee_yazeed-20231001T170032.h5 - SXCT scan of a wasp performed at beamline <a href="https://www.sesame.org.jo/beamlines/beats">ID10-BEATS</a> of SESAME.</li><li>SESAME_wasp_yazeed.avi - 3D video rendering of phase-contrast CT reconstruction of bee_yazeed-20231001T170032. The dataset was reconstructed using <a href="https://github.com/gianthk/alrecon/tree/master">alrecon</a>. The video was created using ORS Dragonfly.</li></ul><h4>H5 dataset information:</h4><ul><li>Raw experimental data (sinogram, flat fields and dark fields) and metadata are stored in a common .H5 file.</li><li>The HDF5 file is organized hierarchically following the <a href="https://dxfile.readthedocs.io/en/latest/">Scientific Data Exchange (DXfile)</a> community standard.</li></ul><h4>How to reconstruct:</h4><ul><li>You can use <a href="http://www.silx.org/">Silx</a> to read and explore the .H5 dataset.</li><li>The file can be read within Python using the <a href="https://dxchange.readthedocs.io/en/latest/">DXChange</a> package.</li><li>See the <a href="https://beats.readthedocs.io/reconstruction.html">ID10-BEATS beamline user guide</a> for a detailed description on how to process and reconstruct the scan.</li></ul>

opencc-by-4.0Mar 2022View details →

Data for "Measurement of temperature induced X-ray tube transmission target displacements for dimensional computed tomography"

Raw data used to create figures for the paper "Measurement of temperature induced X-ray tube transmission target displacements for dimensional computed tomography" <a href="https://doi.org/10.1016/j.precisioneng.2021.06.002">https://doi.org/10.1016/j.precisioneng.2021.06.002</a> Data is available in tab delimited format (.txt) and in Excel (.xls).

opencc-by-4.0Feb 2022View details →

Simulated X-ray micro-computed tomography based particle tracking velocimetry dataset for validation purposes

Authors: Tom Bultreys, Stefanie Van Offenwert, Wannes Goethals, Matthieu N. Boone, Jan Aelterman and Veerle Cnudde; Ghent University (Belgium) Date: 8th February 2022 For any usage, please cite the accompanying publication: T. Bultreys, S. Van Offenwert, W. Goethals, M. N. Boone, J. Aelterman and V. Cnudde, "X-ray Tomographic Micro-Particle Velocimetry in Porous Media", Physics of Fluids, 34, 042008 (2022). https://doi.org/10.1063/5.0088000 ----------------------------- Validation dataset for micro-computed tomography based particle tracking velocimetry: a simulated micro-CT based velocimetry experiment with associated ground-truth particle trajectories - The ground truth trajectories were based on randomly dropping virtual particles in the pore space, and tracking their movement through a CFD-based velocity field (see below). The positions were calculated for the time corresponding to each radiograph of a micro-CT experiment. The folder "GroundTruthData" contains the locations of all particles at the central time of each micro-CT scan, as well as their radii. Check the associated readme file to read the data file. - The main data is contained in the directory "TimeFrames", containing the reconstructed 3D images at 7 time steps (70 seconds interval), with a voxel size of 11.8 µm, in 3D .tif format. This can be opened in for example Fiji/ImageJ. - The directory "clearFrame" contains an image of the pore space without particles, matching with the time frame images, in the same format and with the same voxel size as the time frame images. - The directory "SegmentedImage" contains two binary 3D images (same format as images before) which was created by segmenting the clearFrame image. There are two versions: the original segmentation, and a version where pores were eroded. The eroded segmentation was used to mask the pore space during particle detection (this avoids spurious detections near pore walls, caused by minor mis-alignments of the clearImage). - The original segmentation was used as input to simulate the velocity fields in the directory "simulatedVelocityFields", which contains 3D .tif images that represent the three components of the velocity vector field (the X-direction was the axis of the sample, equaling the flow direction). There is also an input text file and an output text file. The simulation was performed with the code from single-phase OpenFOAM implementation from Ali Raeini and others at Imperial College London: http://www.imperial.ac.uk/earth-science/research/research-groups/perm/research/pore-scale-modelling/ - The trackingOutput folder contains the experimentally determined velocity points (.csv, only particles that could be tracked at least 6 time frames) and the experimentally determined velocity magnitude field (.tif, voxel size 23.6 µm)

opencc-by-4.0Feb 2022View details →

X-ray micro-computed tomography based X-ray particle tracking velocimetry dataset in a porous glass filter

Authors: Tom Bultreys, Stefanie Van Offenwert, Wannes Goethals, Matthieu N. Boone, Jan Aelterman and Veerle Cnudde; Ghent University (Belgium) Date: 8th February 2022 For any usage, please cite the accompanying publication: T. Bultreys, S. Van Offenwert, W. Goethals, M. N. Boone, J. Aelterman and V. Cnudde, "X-ray Tomographic Micro-Particle Velocimetry in Porous Media", Physics of Fluids, 34, 042008 (2022). https://doi.org/10.1063/5.0088000 ----------------------------- Dataset of a micro-computed tomography based particle tracking velocimetry experiment performed on a glass filter (ROBU P0; sample size 4 mm diameter by 1 cm). - The main data is contained in the directory "TimeFrames", containing the reconstructed 3D images at 59 time steps (35 seconds interval), with a voxel size of 11.8 µm, in 3D .tif format. This can be opened in for example Fiji/ImageJ. - The directory "clearFrame" contains a high-quality pre-scan taken before the main experiment, which was registered and resampled to the time frame images, in the same format and with the same voxel size as the time frame images. - The directory "SegmentedImage" contains two binary 3D images (same format as images before) which was created by segmenting the clearFrame image. There are two versions: the original segmentation, and a version where pores were eroded. The eroded segmentation was used to mask the pore space during particle detection (this avoids spurious detections near pore walls, caused by minor mis-alignments of the clearImage). - The original segmentation was used as input to simulate the velocity fields in the directory "simulatedVelocityFields", which contains 3D .tif images that represent the three components of the velocity vector field (the X-direction was the axis of the sample, equaling the flow direction). There is also an input text file and an output text file. The simulation was performed with the code from single-phase OpenFOAM implementation from Ali Raeini and others at Imperial College London: http://www.imperial.ac.uk/earth-science/research/research-groups/perm/research/pore-scale-modelling/ - The trackingOutput folder contains the experimentally determined velocity points (.csv, only particles that could be tracked at least 20 time frames) and the experimentally determined velocity magnitude field (.tif, voxel size 23.6 µm)

opencc-by-4.0Feb 2022View details →

X-ray micro-computed tomography based particle tracking velocimetry dataset in a sandpack

Authors: Tom Bultreys, Stefanie Van Offenwert, Wannes Goethals, Matthieu N. Boone, Jan Aelterman and Veerle Cnudde; Ghent University (Belgium) Date: 8th February 2022 For any usage, please cite the accompanying publication: T. Bultreys, S. Van Offenwert, W. Goethals, M. N. Boone, J. Aelterman and V. Cnudde, "X-ray Tomographic Micro-Particle Velocimetry in Porous Media", Physics of Fluids, 34, 042008 (2022). https://doi.org/10.1063/5.0088000 ----------------------------- Dataset of a micro-computed tomography based particle tracking velocimetry experiment performed on a sand pack (grainsize 500-710 µm; sample size 4 mm diameter by 2 cm). - The main data is contained in the directory "TimeFrames", containing the reconstructed 3D images at 79 time steps (35 seconds interval), with a voxel size of 11.8 µm, in 3D .tif format. This can be opened in for example Fiji/ImageJ. - The directory "clearFrame" contains a high-quality pre-scan taken before the main experiment, which was registered and resampled to the time frame images, in the same format and with the same voxel size as the time frame images. - The directory "SegmentedImage" contains two binary 3D images (same format as images before) which was created by segmenting the clearFrame image. There are two versions: the original segmentation, and a version where pores were eroded. The eroded segmentation was used to mask the pore space during particle detection (this avoids spurious detections near pore walls, caused by minor mis-alignments of the clearImage). - The original segmentation was used as input to simulate the velocity fields in the directory "simulatedVelocityFields", which contains 3D .tif images that represent the three components of the velocity vector field (the X-direction was the axis of the sample, equaling the flow direction). There is also an input text file and an output text file. The simulation was performed with the code from single-phase OpenFOAM implementation from Ali Raeini and others at Imperial College London: http://www.imperial.ac.uk/earth-science/research/research-groups/perm/research/pore-scale-modelling/ - The trackingOutput folder contains the experimentally determined velocity points (.csv, only particles that could be tracked at least 20 time frames) and the experimentally determined velocity magnitude field (.tif, voxel size 23.6 µm)

opencc-by-4.0Apr 2022View details →

HandCT: hands-on computational dataset for X-Ray Computed Tomography

HandCT is a computational dataset to train machine-learning models for X-Ray Computed Tomography (CT). It consists of a meshed hand model, of which pose and anatomical properties are computed at run-time from a script. As such, it is an accurate modeling of anatomical phantoms of only 1.35 mB, and reproducibility is ensured using random seeds. It allows the user to have full control over the imaging chain, from projection to reconstruction, and over the X-Ray interaction with the different parts of the model by a simple variable editing. This open-source solution relies on the freeware Blender for the modelling and Python for the computations. The first deals with modelling, rigging and deformations, whilst the later ensures transformations such as scaling, translation, or else forward projection. This dataset can be used to train and evaluate regularisation procedures for low-energy, dual-energy and scarce-view CT.

openmit-licenseJul 2019View details →

Code and Data from: Segmenting Root Systems in X-Ray Computed Tomography Images Using Level Sets

This record contains code and data for segmentation using a three-dimensional level-set method, written by Amy Tabb in C++.  The record also contains two datasets of root systems in media imaged with X-Ray CT, and the results of running the code on those datasets.  The code will also perform a pre-processing task in three-dimensional image sets, and a dataset for that purpose is included as well.  This work is a companion to the paper : "Segmenting root systems in X-ray computed tomography images using level sets" (WACV 2018) by the authors or this record, and and open-access version of the paper is here -- https://arxiv.org/abs/1809.06398 .   The code is also available from Github: https://github.com/amy-tabb/tabb-level-set-segmentation , using a DOI and stable releases https://doi.org/10.5281/zenodo.3344906. Format of the data: Three input datasets are provided; two for the segmentation functionality of the code, and one to test the pre-processing functionality.  The two segmentation sets are the same as were used in the paper, and are CassavaDataset, and SoybeanDataset.  The pre-processing set is CassavaSlices.  The output set for Soybean is SoybeanResultsJul11.  The Cassava result set is large, so I broke it into three compressed folders, CassavaResultsJul12_A, _B, _C.  _B is the largest, and only contains the results overwritten on the original X-Ray images.  Unless your connection to Zenodo is extremely fast, it will be faster to compute the result than to download it.

Zinc Doped Zeolite 13X I13-2 X-Ray Computed Tomography - 0.325 micron pixel size RAW

This repository contains raw data for the zinc-doped zeolite 13X sample imaged on the I13-2 beamline at Diamond Light Source. Raw data at a pixel-size of 0.325 microns is stored as a .nxs file, and a savu process list is provided to perform the reconstruction we used to reproduced the reconstructed data. This data is one of four resolutions obtained. A detailed data descriptor pre-print is available at https://arxiv.org/abs/2409.07322# The size of the .hdf file is >50GB and cannot be downloaded from the browser. It is recommended to use a terminal to download the data using the 'curl' or 'wget' command. To generate a file url, right-click the 'Download' button for the dataset you want to download and select 'Copy Link. Enter the following command in your terminal to download the dataset: <blockquote> curl dataset_url > 169065_raw.hdf </blockquote> Please replace dataset_url with the url you copied.

Zinc Doped Zeolite 13X I13-2 X-Ray Computed Tomography - 1.625 micron pixel size RAW

This repository contains raw data for the zinc-doped zeolite 13X sample imaged on the I13-2 beamline at Diamond Light Source. Raw data at a pixel-size of 1.625 microns is stored as a .nxs file, and a savu process list is provided to perform the reconstruction we used to reproduced the reconstructed data. This data is one of four resolutions obtained. A detailed data descriptor pre-print is available at https://arxiv.org/abs/2409.07322# The size of the .hdf file is >50GB and cannot be downloaded from the browser. It is recommended to use a terminal to download the data using the 'curl' or 'wget' command. To generate a file url, right-click the 'Download' button for the dataset you want to download and select 'Copy Link. Enter the following command in your terminal to download the dataset: <blockquote> curl dataset_url > 169067_raw.hdf </blockquote> Please replace dataset_url with the url you copied.

Zinc Doped Zeolite 13X I13-2 X-Ray Computed Tomography - 2.6 micron pixel size RAW

This repository contains raw data for the zinc-doped zeolite 13X sample imaged on the I13-2 beamline at Diamond Light Source. Raw data at a pixel-size of 2.6 microns is stored as a .nxs file, and a savu process list is provided to perform the reconstruction we used to reproduced the reconstructed data. This data is one of four resolutions obtained. A detailed data descriptor pre-print is available at https://arxiv.org/abs/2409.07322# The size of the .hdf file is >50GB and cannot be downloaded from the browser. It is recommended to use a terminal to download the data using the 'curl' or 'wget' command. To generate a file url, right-click the 'Download' button for the dataset you want to download and select 'Copy Link. Enter the following command in your terminal to download the dataset: <blockquote> curl dataset_url > 169068_raw.hdf </blockquote> Please replace dataset_url with the url you copied.

Zinc Doped Zeolite 13X DIAD X-Ray Diffraction Computed Tomography - 25 and 50 micron spot-size

This repository contains X-Ray Diffraction Computed Tomography (XRD-CT) data of a zinc doped zeolite 13X sample on the Dual Imaging and Diffraction (DIAD / K11) at Diamond Light Source. XRD-CT data is provided at a diffraction spot size of 25 microns for three region of interest slices, with a dataset size of 40x2000x80. Both the raw and reconstructed data is provided, along with the code to perform the reconstructions.  XRD-CT data is also provided at a diffraction spot size of 50 microns for a full 1.05mm volume, with a dataset size of 20x2000x40. Scans start at 43336 and finish at 43401, with a movement of 0.05mm vertically upwards between each scan. The raw and reconstructed data is provided, along with the code used to perform the reconstructions. Note: Scan 43401 is excluded as a phase-based reconstruction could not be performed. Powder X-Ray Diffraction data can be found in an alternative repository at 10.5281/zenodo.13329670 which provides the q-values of the peaks for both the Zn and Na phase to allow the best reconstructions. A detailed data descriptor pre-print can be found at https://arxiv.org/abs/2409.07322

Zinc Doped Zeolite 13X I13-2 X-Ray Computed Tomography - 0.8125 micron pixel size RAW

This repository contains raw data for the zinc-doped zeolite 13X sample imaged on the I13-2 beamline at Diamond Light Source. Raw data at a pixel-size of 0.8125 microns is stored as a .nxs file, and a savu process list is provided to perform the reconstruction we used to reproduced the reconstructed data. This data is one of four resolutions obtained. A detailed data descriptor pre-print is available at https://arxiv.org/abs/2409.07322# The size of the .hdf file is >50GB and cannot be downloaded from the browser. It is recommended to use a terminal to download the data using the 'curl' or 'wget' command. To generate a file url, right-click the 'Download' button for the dataset you want to download and select 'Copy Link. Enter the following command in your terminal to download the dataset: <blockquote> curl dataset_url > 169066_raw.hdf </blockquote> Please replace dataset_url with the url you copied.