Using algebraic reconstruction in computed tomography

  • Authors:

  • Nate D. Tang;Niels de Ruiter;J. L. Mohr;A. P. H. Butler;P. H. Butler;R. Aamir

  • Affiliations:

  • University of Canterbury, Christchurch, New Zealand;University of Otago, Christchurch, New Zealand;University of Otago, Christchurch, New Zealand;University of Otago, Christchurch, New Zealand;University of Canterbury, Christchurch, New Zealand;University of Canterbury, Christchurch, New Zealand

  • Venue:
  • Proceedings of the 27th Conference on Image and Vision Computing New Zealand
  • Year:
  • 2012

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Abstract

Spectral Computed Tomography (spectral CT) is a newly emerging, medical imaging modality. It extends CT by acquiring multiple datasets over different x-ray energy bins. As the x-ray absorption of materials is energy dependent, the energy bins together provide significantly more information about the composition of the subject. To exploit the full potential of spectral CT, there are many new image processing challenges for reconstruction, material decomposition, and visualization. This paper details the preliminary work completed before a spectral reconstruction algorithm may be developed. A small application called mART was created which implements a Simultaneous Algebraic Reconstruction Technique (SART). The algorithm SART will be extended for spectral reconstruction in the near future. We show that mART already produces reconstructions of superior quality to Octopus CT® which is the commercial software adopted by the MARS team. In addition, ideas for developing a spectral reconstruction algorithm are discussed.