DOI: 10.5281/zenodo.4212300
title: Apple CT Data: Simulated parallel-beam tomographic datasets

description: <strong>Summary</strong> This submission is a supplementary material to the article [Coban 2020b]. As part of the manuscript, we release three simulated parallel-beam tomographic datasets of 94 apples with internal defects, the ground truth reconstructions and two defect label files. <strong>Description</strong> This Zenodo upload contains the three simulated datasets, Datasets A-C, and the two defect label files. The three versions are a noiseless simulation (Dataset A); simulation with added Gaussian noise (Dataset B), and with scattering noise (Dataset C). The datasets are based on real 3D X-ray CT data and their subsequent volume reconstructions. The defect label files contain tables of pixel numbers assigned to each defect present in the apples. Each row in the table corresponds to a single apple, and each column is a defect across the 94 apples. The two defect label files are <em>apple_defects_full.csv</em> and <em>apple_defects_partial.csv</em>: The former containing defect information for a full apple, and the latter for a selection of slices in an apple. The ground truth reconstructions are also available through this project, via 6 separate Zenodo uploads: Apple CT Data: Ground truth reconstructions - 1 of 6 Apple CT Data: Ground truth reconstructions - 2 of 6 Apple CT Data: Ground truth reconstructions - 3 of 6 Apple CT Data: Ground truth reconstructions - 4 of 6 Apple CT Data: Ground truth reconstructions - 5 of 6 Apple CT Data: Ground truth reconstructions - 6 of 6 The datasets are prepared for development and testing of data-driven, learning-based image reconstruction, segmentation and post-processing methods. <strong>Simulation Setup</strong> Each projection in Datasets A-C contains 50 angles, taken over 180 degrees. The projections are evenly distributed over the half circle, with an angular increment of 3.6 degrees. The size of the projections is 50px x 1377px. In total we have 62792 projections for Datasets A and B, and 7520 for Dataset C. All projections are in .tif format. We also include <em>proj_angs.txt </em>containing a list of projection angles in radians. These projection angles are the same for all three datasets. <strong>List of Contents</strong> The contents of the submission is given below. <strong>Dataset_A: </strong> Simulated parallel-beam projections, each named as "<em>data_appleNo_sliceNo.tif</em>". <strong>Dataset_B: </strong> Dataset A with added 5% Gaussian noise, each named "<em>data_noisy_appleNo_sliceNo.tif</em>". <strong>Dataset_C: </strong> Dataset A with added scattering for a selection of slices, each named "<em>data_appleNo_sliceNo.tif</em>". <em>proj_angs.txt: </em>List of projection angles for all datasets. <em>apple_defects_full.csv:</em> The label defect information (in pixel numbers) for each apple for all slices. <em>apple_defects_partial.csv: </em>The label defect information (in pixel numbers) for each apple for a selection of slices. <strong>Additional Links</strong> 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. <strong>Contact Details</strong> For more information or guidance in using these dataset, please get in touch with s.b.coban [at] cwi.nl vladyslav.andriiashen [at] cwi.nl poulami.ganguly [at] cwi.nl <strong>Acknowledgments</strong> We acknowledge GREEFA for supplying the apples and further discussions.
description: S.B.C. would like to acknowledge the financial support of the Netherlands Organisation for Scientific Research (NWO; project number 639.073.506); P.S.G. the Marie Skłodowska-Curie Innovative Training Network MUMMERING (grant agreement no. 765604)
description: {"references": ["Coban SB, Lucka F, Palenstijn WJ, Van Loo D, Batenburg KJ. Explorative Imaging and Its Implementation at the FleX-ray Laboratory. Journal of Imaging. 2020; 6(4):18. https://doi.org/10.3390/jimaging6040018", "Coban, S.B., Andriiashen, V., Ganguly, P.S., van Eijnatten, M., Trull, A.K., Berendsen, F.F., Batenburg, K.J. Parallel-beam X-ray CT datasets of apples with internal defects and label balancing for machine learning. arXiv preprint. 2020. https://arxiv.org/abs/2012.13346"]}