Image reconstruction in dynamic inverse problems with temporal models

Hauptmann, Andreas; Öktem, Ozan; Schönlieb, Carola (2021-12-08)
 
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https://doi.org/10.1007/978-3-030-03009-4_83-1

Hauptmann, Andreas
Öktem, Ozan
Schönlieb, Carola
Springer
08.12.2021

Hauptmann A., Öktem O., Schönlieb C. (2021) Image Reconstruction in Dynamic Inverse Problems with Temporal Models. In: Chen K., Schönlieb CB., Tai XC., Younces L. (eds) Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging. Springer, Cham. https://doi.org/10.1007/978-3-030-03009-4_83-1

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© 2021 Springer. This is a post-peer-review, pre-copyedit version of an article published in Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging. The final authenticated version is available online at https://doi.org/10.1007/978-3-030-03009-4_83-1.
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doi:https://doi.org/10.1007/978-3-030-03009-4_83-1
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https://urn.fi/URN:NBN:fi-fe2021122262999
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Abstract

This paper surveys variational approaches for image reconstruction in dynamic inverse problems. Emphasis is on variational methods that rely on parametrized temporal models. These are encoded here as diffeomorphic deformations with time-dependent parameters or as motion-constrained reconstructions where the motion model is given by a differential equation. The survey also includes recent developments in integrating deep learning for solving these computationally demanding variational methods. Examples are given for 2D dynamic tomography, but methods apply to general inverse problems.

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