Summary: This submission contains two (single-tile and two-tile) tomographic dataset of the terracotta object, the "Torso". This data was collected as part of a larger project including a series of similar terracotta objects (of various body parts), more information can be found in [Scholten 2014]. The data is made available as part of Case Study 1 in [Coban 2020].

Apparatus: The dataset is acquired using the custom-built and highly flexible CT scanner, FleX-ray Laboratory, developed by TESCAN-XRE, located at CWI in Amsterdam. This apparatus consists of a cone-beam microfocus X-ray point source that projects polychromatic X-rays onto a 1944-by-1536 pixels, 14-bit, flat detector panel. Full details can be found in [Coban 2020].

Sample Information: The sample is a terracotta object from the series of various body parts collection by the sculptor Johan Gregor van der Schardt. The sample in particular is called "Torso", which is a hollow clay statue, originally believed to have been created using two moulds of clay put together. The sample was mounted in a bed of foam, and secured with 2 thin plastic sticks through the legs of the statue. This was done to dampen any vibrations from the rotation while the statue is mounted upright. See Figure 4 in [Coban 2020] for photos of the sample in mount.

Experimental Plan: The data in this submission was collected via the technique of explorative imaging, in which data is collected upon discussion with the expert and any intermediate reconstruction results. The experiments included in this upload first starts off with a single tile, binned acquisition. The sample is then zoomed in and data is collected in two halves (two detector tiles) to capture details in higher resolution. More information on this process is given in Section 3.1 in [Coban 2020]. For both experiments, the sample is rotated 360° in circular and continuous motion, with a dark-field (closed-shutter), and 2 flat-field (open-shutter) images taken before and after the acquisition. For the first experiment, single-tile, we collected 1200 projections at 136 micron resolution (size of each pixel on detector plane). For the second experiment, the object was moved closed to the source, and the data was collected in two tiles (spatial tiles in detector space). Each tiled-data folder contains 2001 projections at 50 spatial resolution. All raw data (i.e. no corrections) is made available in .tif format.

List of Contents: The contents of the submission is given below. single-tile: A "low" resolution scan, taken to answer the initial question. two-tiles: A higher resolution scan for studying the finer details such as toolmarks on the interior of the statue; contains t1 and t2 for tile 1 (top) and tile 2 (bottom) respectively. Each data folder contains dark-field (or closed-shutter) image, di0000.tif, pre flat-field (or open-shutter before acqusition) image, io0000.tif, post flat-field (or open-shutter after acqusition) image, io0001.tif, raw (unprocessed or uncorrected) projections, scan_*.tif, data settings XRE.txt, a text file with scanner metadata, scan settings.txt, a text file with scanner metadata in more human readeable format, and data settings XRE.ini, a snapshot text file of basic geometry information at the start of a scan. script.txt and script_executed.txt are the text files containing the list of commands the apparatus has executed.

Additional Links: These datasets are produced by the Computational Imaging group at Centrum Wiskunde & Informatica (CI-CWI). For any relevant Python/MATLAB scripts for the FleX-ray datasets, we refer the reader to our group's GitHub page.

Contact Details: For more information or guidance in using these dataset, please get in touch with s.b.coban [at] cwi.nl

Acknowledgments: We thank Isabelle Garachon of Rijksmuseum for providing this extra-ordinary sample.

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doi.org/10.5281/zenodo.3630710
Real-Time 3D Tomography
creativecommons.org/licenses/by/4.0/legalcode
Computational Imaging

Coban, S.B. (2017). A single- and two-tile tomographic micro-CT data of the terracotta sculpture "the Torso". doi:10.5281/zenodo.3630710