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CT reconstruction and structured light scan of a small wooden block

<p><strong>Summary</strong></p><p>This submission contains a reconstruction from a tomographic dataset and a structured light scan of a small wooden block.</p><p>The data is made available as part of [Bossema et al., 2023] and is meant to serve as a practice dataset for the Blender plugin that is published along the article. The code for the plugin can be found here and on github. &nbsp;&nbsp;</p><p>&nbsp;</p><p><strong>Apparatus</strong></p><p>The CT 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&nbsp;pixels, 14-bit, flat detector panel. Full details can be found in [Coban et al., 2020].</p><p>The structured light scan was acquired using an Artec Spider.</p><p><strong>Sample Information</strong></p><p>The sample is small wooden block (6x5x3cm).</p><p><strong>List of Contents</strong></p><p>The content of the submission is given below.</p><ul><li><strong>CT_intact_woodblock_130micron:</strong> CT reconstruction, TIFF files, resolution 130 micron.</li><li><strong>Surface_intact_woodblock: </strong>structured light scan</li></ul><p>Acquisition details can be found in the supplementary material of [Bossema et al, 2023]</p><p>These&nbsp;datasets are&nbsp;produced by the&nbsp;Computational Imaging group&nbsp;at Centrum Wiskunde &amp; Informatica (CI-CWI), in collaboration with Rijksmuseum Amsterdam.</p><p><strong>Contact Details</strong></p><p>For more information or guidance in using these datasets, please get in touch with&nbsp;</p><ul><li>bossema [at] cwi.nl</li></ul><p>&nbsp;</p><p><strong>Acknowledgements</strong></p><p>The authors would like to acknowledge the funding from the Netherlands Organisation for Scientific Research (NWO), project numbers 341-60-001, 639.073.506 and 628.007.033 and Netherlands Institute for Conservation, Art and Science (NICAS).</p>

ShareScore

36/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
4
Harmonization
8
Access
16
Reuse readiness
8
Engagement
0

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