An Iterative CT Reconstruction Algorithm for Fast Fluid Flow Imaging

Geert Van Eyndhoven, K. Joost Batenburg, Daniil Kazantsev, Vincent Van Nieuwenhove, Peter D. Lee, Katherine J. Dobson, Jan Sijbers

Research output: Contribution to journalArticlepeer-review

35 Citations (Scopus)


The study of fluid flow through solid matter by computed tomography (CT) imaging has many applications, ranging from petroleum and aquifer engineering to biomedical, manufacturing, and environmental research. To avoid motion artifacts, current experiments are often limited to slow fluid flow dynamics. This severely limits the applicability of the technique. In this paper, a new iterative CT reconstruction algorithm for improved a temporal/spatial resolution in the imaging of fluid flow through solid matter is introduced. The proposed algorithm exploits prior knowledge in two ways. First, the time-varying object is assumed to consist of stationary (the solid matter) and dynamic regions (the fluid flow). Second, the attenuation curve of a particular voxel in the dynamic region is modeled by a piecewise constant function over time, which is in accordance with the actual advancing fluid/air boundary. Quantitative and qualitative results on different simulation experiments and a real neutron tomography data set show that, in comparison with the state-of-the-art algorithms, the proposed algorithm allows reconstruction from substantially fewer projections per rotation without image quality loss. Therefore, the temporal resolution can be substantially increased, and thus fluid flow experiments with faster dynamics can be performed.

Original languageEnglish
Article number7182322
Pages (from-to)4446-4458
Number of pages13
JournalIEEE Transactions on Image Processing
Issue number11
Early online date7 Aug 2015
Publication statusPublished - 30 Nov 2015


  • ct
  • fluid flow experiments
  • iterative reconstruction
  • neutron tomography


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