Bayesian reconstruction of functional images using registered anatomical images as priors

  • G Gindi
  • M Lee
  • A Rangarajan
  • I G Zubal
2. Incorporation Of Priors In Tomographic Reconstraction
Part of the Lecture Notes in Computer Science book series (LNCS, volume 511)


We propose a Bayesian method whereby MAP estimates of functional (PET and SPECT) images may be reconstructed with the aid of prior information derived from registered anatomical (CT and MRI) images of the same slice. Our prior information consists of significant anatomical boundaries that are likely to correspond to discontinuities in an otherwise spatially smooth radionuclide distribution. Our algorithm, like others proposed recently, seeks smooth solutions with occasional discontinuities; the contribution here is the inclusion of a coupling term that influences the creation of discontinuities in the vicinity of the significant anatomical boundaries. Simulations on anatomically derived mathematical phantoms are presented. The reconstructions are greatly improved when the prior information is used.


Multimodality SPECT CT PET MRI Data fusion Markov Random field 


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Copyright information

© Springer-Verlag Berlin Heidelberg 1991

Authors and Affiliations

  • G Gindi
    • 1
    • 2
  • M Lee
    • 2
  • A Rangarajan
    • 1
    • 3
  • I G Zubal
    • 1
  1. 1.Division of Imaging Science Department of Diagnostic RadiologyYale UniversityNew Haven
  2. 2.Department of Electrical EngineeringYale UniversityYale Station, New Haven
  3. 3.Department of Computer ScienceYale UniversityNew Haven

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