Abstract
Gated 4D cardiac imaging with C-arm CT scanners suffers from insufficient image quality due to strong angular undersampling. To deal with this problem, we suggest an iterative reconstruction method with spatial and temporal total variation regularization based on an established framework which controls the relative contributions of raw data error minimization and regularization. This new method is tested on a simulated heart phantom and on two clinical data sets. We show that the additional use of temporal regularization is advantageous compared to spatial regularization exclusively, with the relative root mean square error lowered from 11.75% to 8.24% in the phantom study.
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© 2016 Springer-Verlag Berlin Heidelberg
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Haase, V. et al. (2016). Make the Most of Time Temporal Extension of the iTV Algorithm for 4D Cardiac C-Arm CT. In: Tolxdorff, T., Deserno, T., Handels, H., Meinzer, HP. (eds) Bildverarbeitung für die Medizin 2016. Informatik aktuell. Springer Vieweg, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-49465-3_31
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DOI: https://doi.org/10.1007/978-3-662-49465-3_31
Publisher Name: Springer Vieweg, Berlin, Heidelberg
Print ISBN: 978-3-662-49464-6
Online ISBN: 978-3-662-49465-3
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