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Spectral CT reconstruction with anti-correlated noise model and joint prior

Mats Persson, Jonas Adler

DOI:10.12059/Fully3D.2017-11-3203027

Published in:Fully3D 2017 Proceedings

Pages:580-585

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Spectral CT allows reconstructing a set of material selective basis images which can be used for material quantification. These basis images can be reconstructed independently of each other or treated as a joint reconstruction problem. In this work, we investigate the effect of two ways of introducing coupling between the basis images: using an anti-correlated noise model and regularizing the basis images with a joint prior. We simulate imaging of a FORBILD Head phantom with an ideal photon-counting detector and reconstruct the resulting basis sinograms with and without these two kinds of coupling. The results show that the anti-correlated noise model gives better spatial resolution than the uncorrelated noise model at the same noise level, but also introduces artifacts. If anti-correlations are introduced also in the prior, these artifacts are reduced and the resolution is improved further.
Mats Persson
Departments of Bioengineering and Radiology, Stanford University
Jonas Adler
KTH Royal Institute of Technology
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