Image Reconstruction Using A Priori Boundary Information

Valen E. Johnson, Chin-Tu Chen, Xiaoping Hu, Wing H. Wong
Duke University, University of Chicago

Nov 30 1989

We describe a Bayesian model for the reconstruction of images based on projection data. The model incorporates a boundary process to sever correlation between neighboring regions with images, and the prior distribution of the boundary process can be modified easily in situation in which precise boundary information is available a priori. An example of a positron emission tomography image recontructed using boundaries obtained form a high resolution magnetic resonance image is provided.


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