Micro-CT dataset of Rijksmuseum cornett bottom half (1/2)

<p><strong><span>Summary</span></strong></p> <p><span>This submission contains a micro-CT reconstruction of a cornett from the Rijksmuseum collection (obj. nr. </span><span>BK-AM-62-B; <a href="https://www.rijksmuseum.nl/nl/collectie/BK-AM-62-B">https://www.rijksmuseum.nl/nl/collectie/BK-AM-62-B</a>)</span><span>. </span><span>This dataset contains tile 1-8 (out of 15), dataset 1 (out of 2) covering the bottom half of the cornetto.</span></p> <p><span>The data relates to [Bossema, 2021], [Dorscheid, 2022] and [Van Liere, 2022]. </span></p> <p><em><span>&nbsp;</span></em></p> <p><strong><span>Apparatus</span></strong></p> <p><span>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&nbsp;pixels, 14-bit, flat detector panel. Full details can be found in [Coban, 2020].</span></p> <p><em><span>&nbsp;</span></em></p> <p><strong><span>Sample Information</span></strong></p> <p><span>The sample is cornett</span><span>, </span><span><span>height 56.0 cm x width 10.0 cm x diameter 3.5 cm</span></span><span> , </span><span>c. 1600 - c. 1650</span><span> </span><span>[</span><span>Rijksmuseum inventory number</span><span> BK-NM-62-B, </span><span><span>&nbsp;</span></span><span>https://www.rijksmuseum.nl/nl/collectie/BK-AM-62-B</span><span>]. </span><span>It was mounted in a custom made foam stand on the rotation stage. <span>&nbsp;</span>See Figure 10 in [Bossema, 2021] for a picture of the object and the mount and </span><span>results [Bossema, 2021], [Dorscheid, 2022] and [Van Liere, 2022] </span><span>for analysis of the reconstructed images. <em>&nbsp;<br><br></em></span></p> <p><strong><em><span>Experimental Plan</span></em></strong></p> <p><span>The data in this submission was collected to illustrate the scanning process to iteratively include feedback from cultural heritage experts [Bossema, 2021] and was later used for a detailed investigation of the current state and earlier restoration treatments [Dorscheid, 2022] and for illustrating the dual space method [Van Liere, 2022].</span></p> <p><span>To image the entire object, thirty tiles were scanned with SOD = 734 and SDD = 1098, in two sessions of 15 tiles (5 vertical, 3 horizontal). For each scan, the sample was rotated 360&deg; in circular and continuous motion, with a dark-field (closed-shutter), and flat-field (open-shutter) images taken before the acquisition. The datasets of each tile consist of 1200 projections, at 70kV, 42W, 300ms exposure time. </span></p> <p><span>For the reconstructed CT volume, see </span><span>10.5281/zenodo.14265065</span><span>. </span></p> <p><span>&nbsp;</span></p> <p><strong><span>List of Contents</span></strong></p> <p><span>This dataset contains tile 1-8 (out of 15), dataset 1 (out of 2) covering the bottom half of the cornetto.</span></p> <p><span>Each tile data folder (T*) contains:</span></p> <ul> <li><span>dark-field (or closed-shutter) image,&nbsp;<em>di000000.tif</em>,</span></li> <li><span>flat-field (or open-shutter) image before acquisition,&nbsp;<em>io000000.tif</em></span></li> <li><span>raw (unprocessed or uncorrected) projections,&nbsp;<em>scan_*.tif</em>,</span></li> <li><em><span>data settings XRE.txt</span></em><span>, a text file with scanner metadata</span></li> </ul> <p><strong><span>Additional Links</span></strong></p> <p><span>These&nbsp;datasets are&nbsp;produced by the&nbsp;</span><span><a><span>Computational Imaging group</span></a></span><span>&nbsp;at Centrum Wiskunde &amp; Informatica (CI-CWI). For any relevant Python/MATLAB scripts for the FleX-ray datasets, we refer the reader to our group's&nbsp;</span><span><a><span>GitHub page</span></a></span><span>.</span></p> <p><em><span>&nbsp;</span></em></p> <p><strong><span>Contact Details</span></strong></p> <p><span>For more information or guidance in using these datasets, please get in touch with&nbsp;</span></p> <ul> <li><span>bossema [at] cwi.nl</span></li> </ul> <p><em><span>&nbsp;</span></em></p> <p><strong><span>Acknowledgments</span></strong></p> <p><span>The authors would like to acknowledge the funding from the Netherlands Organisation for Scientific Research (NWO), project numbers </span><span>341-60-001, </span><span>639.073.506 and </span><span>628.007.033 and Netherlands Institute for Conservation, Art and Science (NICAS).</span></p> <p><span>&nbsp;</span></p> <p><strong><span>References</span></strong></p> <p><span>S. B. Coban, F. Lucka, W. J. Palenstijn, D. Van Loo, and K. J. Batenburg, &ldquo;Explorative imaging and its implementation at the FleX-ray Laboratory,&rdquo; <em>J. Imaging</em>, vol. 6, no. 18, 2020, doi: 10.3390/jimaging6040018.</span></p> <p><a href="https://www.sciencedirect.com/science/article/pii/S1296207421000558"><strong><span>F.G.Bossema</span></strong><span>, S.B. Coban, A. Kostenko, P. van Duin, J. Dorscheid, I. Garachon, E. Hermens, R. van Liere, K. J. Batenburg, &ldquo;Integrating expert feedback on the spot in a time-efficient explorative CT scanning workflow for cultural heritage objects&rdquo;, Journal of Cultural Heritage, Vol. 49, p38-47, 2021</span></a></p> <p><a href="https://heritagesciencejournal.springeropen.com/articles/10.1186/s40494-022-00800-8"><span>J. Dorscheid, <strong><span>F.G. Bossema</span></strong>, P. van Duin, S.B. Coban, R. van Liere, K.J. Batenburg, G.P. Di Stefano, &ldquo;Looking under the skin &ndash; multi-scale CT scanning of a peculiarly constructed cornett in the Rijksmuseum&rdquo;, Heritage Science 10, 161 (2022)</span></a></p> <p>R. van Liere, K.J. Batenburg, I. Garachon, C.-L. Wang, J. Dorscheid (2022). <span>The dual space: Concept and applications in cultural heritage. <em><span>IEEE BITS the Information Theory Magazine</span></em>, <em><span>2</span></em>(1), 49&ndash;57. doi:10.1109/MBITS.2022.3202508</span></p> <p><span>Kostenko, A., Palenstijn, W.J., Coban, S.B., Hendriksen, A.A., van Liere, R., Batenburg, K.J.,</span></p> <p><span>2020. Prototyping X-ray tomographic reconstruction pipelines with FleXbox. SoftwareX 11,</span></p> <p><span>100364. https://doi.org/10.1016/j.softx.2019.100364</span></p> <p></p>