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WalnutReconstructionCodes

This is a collection of Python and MATLAB scripts for loading, pre-processing and reconstructing X-ray CT projection data of 42 walnuts as described in

Henri Der Sarkissian, Felix Lucka, Maureen van Eijnatten, Giulia Colacicco, Sophia Bethany Coban, Kees Joost Batenburg, "A Cone-Beam X-Ray CT Data Collection Designed for Machine Learning", Sci Data 6, 215 (2019) or arXiv:1905.04787 (2019)

Henri Der Sarkissian, Felix Lucka, Maureen van Eijnatten, Giulia Colacicco, Sophia Bethany Coban, Kees Joost Batenburg, "A Cone-Beam X-Ray CT Data Collection Designed for Machine Learning", or arXiv:1905.04787 (2019)

  • FDKReconstruction.m and FDKReconstruction.py compute FDK reconstructions for data from a single source-detector orbit, which leads to high cone angle artifacts.
  • GroundTruthReconstruction.m and GroundTruthReconstruction.py compute an iterative reconstructions using the data from all three source-detector orbits, which leads to a reconstruction free of high cone angle artifacts.
  • The complete data set can be found via the following links: 1-8, 9-16, 17-24, 25-32, 33-37, 38-42.

Requirements

  • All scripts make use of the development version (more recent than 1.9.0dev) of the ASTRA toolbox. If you are using conda, this is available through the astra-toolbox/label/dev channel.
  • GroundTruthReconstruction.m makes use of the SPOT toolbox.

Contributors

Henri Der Sarkissian (henri.dersarkissian@gmail.com), Felix Lucka (Felix.Lucka@cwi.nl), CWI, Amsterdam

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Python and MATLAB scripts for computing reconstruction from an openly available X-ray data set

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