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Bayesian Estimation of MR Images from Incomplete Raw Data

  • G. J. Marseille
  • R. de Beer
  • M. Fuderer
  • A. F. Mehlkopf
  • D. van Ormondt
Conference paper
Part of the Fundamental Theories of Physics book series (FTPH, volume 70)

Abstract

This work concerns reduction of the MRI scan time through optimal sampling. We derive optimal sample positions from Cramér-Rao theory. These positions are nonuniformly distributed, which hampers Fourier transformation to the image domain. With the aid of Bayesian formalism we estimate an image that satisfies prior knowledge while its inverse Fourier transform is compatible with the acquired samples. The new technique is applied successfully to a real-world MRI scan of a human brain.

Keywords

Magnetic Resonance Scan Time Reduction Optimal Non-Uniform Sampling Bayesian Estimation Image Reconstruction 

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Copyright information

© Kluwer Academic Publishers 1996

Authors and Affiliations

  • G. J. Marseille
    • 1
  • R. de Beer
    • 1
  • M. Fuderer
    • 2
  • A. F. Mehlkopf
    • 1
  • D. van Ormondt
    • 1
  1. 1.Applied Physics LaboratoryDelft University of technologyDelftThe Netherlands
  2. 2.Philips Medical SystemsBestThe Netherlands

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