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Image Reconstruction Using A Priori Boundary Information

In: Computing Science and Statistics

Author

Listed:
  • Valen E. Johnson

    (Duke University, ISDS)

  • Chin Tu Chen

    (The University of Chicago, Department of Radiology)

  • Xiaoping Hu

    (The University of Chicago, Department of Radiology)

  • Wing H. Wong

    (The University of Chicago, Department of Statistics)

Abstract

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

Suggested Citation

  • Valen E. Johnson & Chin Tu Chen & Xiaoping Hu & Wing H. Wong, 1992. "Image Reconstruction Using A Priori Boundary Information," Springer Books, in: Connie Page & Raoul LePage (ed.), Computing Science and Statistics, pages 151-157, Springer.
    • Handle: RePEc:spr:sprchp:978-1-4612-2856-1_19
    DOI: 10.1007/978-1-4612-2856-1_19
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