Computed tomography with view angle estimation using uncertainty quantification

Nicolai André Brogaard Riis, Yiqiu Dong*, Per Christian Hansen

*Corresponding author for this work

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We consider computed tomography (CT) with uncertain measurement geometry, with a focus on the case where the view angles are uncertain and where estimation of these angles improves the reconstruction. We propose a new reconstruction model and a corresponding algorithm that has an additional view-angle estimation component, allowing us to determine the angles solely from the measured CT data. A key component of our approach is that we quantify the uncertainty of the view angles via a model-discrepancy formulation, allowing us to take the uncertainty into account in the image reconstruction. This approach generalizes in a straightforward way to other cases of uncertain geometry. Our method is computationally efficient since we can utilize a block-structure of the computational problem for estimation of both the CT image and the view angles under the assumption that the view angles are independent. The joint image/angle reconstruction problem is non-convex which leads to difficulties in recently proposed algorithms, and we demonstrate numerically that our method seems to avoid these difficulties. Simulations show that our method, with a total variation prior that reflects our phantoms, is able to achieve reconstructions whose quality is similar to ones obtained with the correct view angles (the ideal scenario).

Original languageEnglish
Article number065007
JournalInverse Problems
Issue number6
Number of pages21
Publication statusPublished - Jun 2021

Bibliographical note

Publisher Copyright:
© 2021 IOP Publishing Ltd.


  • Alternating updates
  • Block representation
  • Computed tomography
  • Uncertainty quantification
  • View angle estimation


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