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Publisher: Zenodo
Type: dataset
Subjects: computed tomography, x-ray, cone beam, reconstruction algorithms, sophiabeads-dataset, segmentation, data correction, large dataset

SophiaBeads Dataset are acquired specifically for testing and comparing reconstruction methods for x-ray computed tomography. The sample is a plastic tube with a diameter of 25mm, filled with uniform Soda-Lime Glass (SiO2-Na2O) beads of diameters 2.5mm (with standard deviation 0.1mm). The sample has been scanned in the same conditions for each dataset, where the number of projections is halved after each batch scan (starting from 2048, down to 64 projections). This allows us to understand the effects of fewer projections, and develop algorithms that deliver quality results when the information content is low (i.e. faster scans or lower dose). 

 

These dataset are also suitable for developing and/or testing

  • segmentation methods,
  • image or data correction techniques (e.g. centre of rotation),
  • forward and back project implementations, and
  • benchmarking user’s own code/method.

 

For the reconstruction and quantification examples, please see (will update with link to paper!)

To use these datasets for own research, please follow the technical report available via (http://eprints.ma.man.ac.uk/2290/), and the GitHub repository (http://sophilyplum.github.io/sophiabeads-datasets/). If publishing work with these datasets, the reader must cite the dataset and the codes separately

 

The dataset are taken using the Nikon Custom Bay machine (using a cone-beam geometry), located in the Manchester Xray Imaging Facility (www.mxif.manchester.ac.uk/resources/imaging-systems/nikon-custom-bay), by Sophia B. Coban and Samuel A. McDonald. 

 

Contact details for authors: 

Sophia B. Coban: 

  • email:
  • website: www.maths.manchester.ac.uk/~scoban

Samuel A. McDonald: 

  • email: 
  • website: http://www.mxif.manchester.ac.uk/index.php/component/comprofiler/userprofile/mclijsm2

 

SophiaBeads Dataset Project Codes (DOI): https://zenodo.org/record/16539

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