Published October 10, 2025 | Version v1
Dataset Open

Static X-ray CT of Various Brands of Spaghetti Noodles

Description

Sample information

 

The dataset consists of a scan of 4 various pasta bundles of different brands (Albert Heijn - Spelt, Albert Heijn - Durum, DeCecco, Gran Italia) placed inside a bottle. The pasta was suspended at the bottleneck using a sponge to hold it in position. Scanning was focused on the bottleneck region. This scan was performed under static conditions: the pasta is suspended in air. The dynamic counterpart of a spaghetti pasta can be found here: 10.5281/zenodo.15688351.

 

Scanner information

The dataset was scanned in the FleX-ray Laboratory located at CWI in Amsterdam. The Flex-ray scanner is custom-built and consists of a cone-beam microfocus X-ray point source.  More system details are available in [Coban 2020].

 

Scanning Settings

The acquisition lasted approximately 6 minutes with a smooth scan type consisting of 2867 projections per full 360° rotation. The setup used a source-to-detector distance (SDD) of 398.99 mm and a source-to-object distance (SOD) of 124.91 mm, resulting in a magnification factor of 3.19 and a voxel size of 23.42 µm. The X-ray tube operated at 50 kV and 40 W in high-power focus mode, with target power output. Images were captured using a detector with an original pixel size of 0.0748 mm and an exposure time of 59.998 ms per frame. For all 4 types of pasta, the same settings were applied.

 

Folder/file name description

There are eight compressed folders in total: four containing the metadata and four containing the corresponding reconstruction files for the scans. The metadata folders include configuration files (e.g., scan_settings.txt) that store the scan parameters and other essential information required for image reconstruction. Each reconstruction folder corresponds to a specific pasta brand and contains 2867 projection images, representing a full 360° rotation. All folders share the same flat-field correction images, which are used for image normalization during the reconstruction process. A script (DeCecco_data_reconstruction.py) is also provided for preprocessing and reconstructing the static volume through the ASTRA toolbox.

 

Research Group

This dataset was produced during a 5-day ASTRA workshop hosted and organized by Leiden University for the RELIANCE Doctoral Network (https://www.chalmers.se/en/projects/reliance/).

 

Contact Details

marychrismcr@liacs.leidenuniv.nl

 

Acknowledgement

This research received funding from Horizon Europe through the MSCA Doctoral Network RELIANCE, grant no. 101073040. 

 

References

[Coban 2020] S. B. Coban, F. Lucka, W. J. Palenstijn, D. Van Loo, and K. J. Batenburg, "Explorative imaging and its implementation at the FleX-ray Laboratory," J. Imaging, vol. 6, no. 18, 2020, doi: 10.3390/jimaging6040018.

[Aarle 2015] W. V. Aarle et al., "The ASTRA toolbox: A platform for advanced algorithm development in electron tomography," Ultramicroscopy, vol. 157, pp. 35–47, 2015.

Files

AHDurum_Metadata.zip

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