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4D-CT reconstruction with unified spatial-temporal patch-based regularization

Kazantsev, D.; Thompson, W.M.; Lionheart, W.R.B.; Van Eyndhoven, G.; Kaestner, A.P.; Dobson, K.J.; Withers, P.J.; Lee, P.D.

4D-CT reconstruction with unified spatial-temporal patch-based regularization Thumbnail


Authors

D. Kazantsev

W.M. Thompson

W.R.B. Lionheart

G. Van Eyndhoven

A.P. Kaestner

K.J. Dobson

P.J. Withers

P.D. Lee



Abstract

Abstract: In this paper, we consider a limited data reconstruction problem for temporarily evolving computed tomography (CT), where some regions are static during the whole scan and some are dynamic (intensely or slowly changing). When motion occurs during a tomographic experiment one would like to minimize the number of projections used and reconstruct the image iteratively. To ensure stability of the iterative method spatial and temporal constraints are highly desirable. Here, we present a novel spatial-temporal regularization approach where all time frames are reconstructed collectively as a unified function of space and time. Our method has two main differences from the state-of-the-art spatial-temporal regularization methods. Firstly, all available temporal information is used to improve the spatial resolution of each time frame. Secondly, our method does not treat spatial and temporal penalty terms separately but rather unifies them in one regularization term. Additionally we optimize the temporal smoothing part of the method by considering the non-local patches which are most likely to belong to one intensity class. This modification significantly improves the signal-to-noise ratio of the reconstructed images and reduces computational time. The proposed approach is used in combination with golden ratio sampling of the projection data which allows one to find a better trade-off between temporal and spatial resolution scenarios.

Citation

Kazantsev, D., Thompson, W., Lionheart, W., Van Eyndhoven, G., Kaestner, A., Dobson, K., …Lee, P. (2015). 4D-CT reconstruction with unified spatial-temporal patch-based regularization. Inverse Problems and Imaging, 9(2), 447-467. https://doi.org/10.3934/ipi.2015.9.447

Journal Article Type Article
Acceptance Date Mar 1, 2015
Online Publication Date Mar 1, 2015
Publication Date May 1, 2015
Deposit Date May 5, 2016
Publicly Available Date Mar 29, 2024
Journal Inverse Problems and Imaging
Print ISSN 1930-8337
Electronic ISSN 1930-8345
Publisher American Institute of Mathematical Sciences (AIMS)
Peer Reviewed Peer Reviewed
Volume 9
Issue 2
Pages 447-467
DOI https://doi.org/10.3934/ipi.2015.9.447

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Copyright Statement
Open Access © 2015 American Institute of Mathematical Sciences





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