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


Spectral CT allows reconstructing a set of materialselective 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.