Dataset Open Access

Apple CT Data: Ground truth reconstructions - 5 of 6

Coban, Sophia Bethany; Andriiashen, Vladyslav; Ganguly, Poulami Somanya

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. 


This Zenodo upload contains the ground truth reconstructed slices for each apple. In total, there are 72192 reconstructed slices, which have been divided into 6 separate submissions:

The simulated parallel-beam datasets and defect label files are also available through this project, via a separate Zenodo upload: 10.5281/zenodo.4212301.

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 2020a].

Ground Truth Generation

We reconstructed the raw tomographic data, which was captured at sample resolution of 54.2µm over a 360 degrees in circular and continuous motion in a cone-beam setup. A total of 1200 projections were collected, which were distributed evenly over the full circle. The raw tomographic data is available upon request.

The ground truth reconstructed slices were generated based on Conjugate Gradient Least Squares (CGLS) reconstruction of each apple. The voxel grid in the reconstruction was 972px x 972px x 768px. The resolution in the ground truth reconstructions remained unchanged.

All ground truth reconstructed slices are in .tif format. Each file is named "appleNo_sliceNo.tif".


List of Contents
The contents of the submission is given below.

  • ground_truths_5: This folder contains reconstructed slices of 16 apples

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]
  • vladyslav.andriiashen [at]
  • poulami.ganguly [at]

We acknowledge GREEFA for supplying the apples and further discussions.

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)
Files (46.4 GB)
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  • 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.

  • 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.

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