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Hierarchical Markov modeling for fusion of X ray radiographic data and anatomical data in computed tomography

We consider an X ray computed tomography (CT) image reconstruction problem where we want to include some geometrical information coming from an anatomical atlas and propose new methods based on hierarchical Markov modeling and a Bayesian estimation approach. We use two kinds of anatomical information: partial knowledge of values in some regions and partial knowledge of the edges of some other regions. We show the advantages of using such information on increasing the quality of reconstructions. We also show some results to analyze the effects of some errors in anatomical data on the reconstructed results.