Detail-Preserving PET Reconstruction with Sparse Image Representation and Anatomical Priors

  • Jieqing Jiao
  • Pawel Markiewicz
  • Ninon Burgos
  • David Atkinson
  • Brian Hutton
  • Simon Arridge
  • Sebastien Ourselin
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9123)


Positron emission tomography (PET) reconstruction is an ill-posed inverse problem which typically involves fitting a high-dimensional forward model of the imaging process to noisy, and sometimes undersampled photon emission data. To improve the image quality, prior information derived from anatomical images of the same subject has been previously used in the penalised maximum likelihood (PML) method to regularise the model complexity and selectively smooth the image on a voxel basis in PET reconstruction. In this work, we propose a novel perspective of incorporating the prior information by exploring the sparse property of natural images. Instead of a regular voxel grid, the sparse image representation jointly determined by the prior image and the PET data is used in reconstruction to leverage between the image details and smoothness, and this prior is integrated into the PET forward model and has a closed-form expectation maximisation (EM) solution. Simulations show that the proposed approach achieves improved bias versus variance trade-off and higher contrast recovery than the current state-of-the-art methods, and preserves the image details better. Application to clinical PET data shows promising results.


PET Image reconstruction Image prior Supervoxels EM 



EPSRC (EP/H046410/1, EP/J020990/1, EP/K005278), the MRC (MR/J01107X/1), the NIHR Biomedical Research Unit (Dementia) at UCL and the National Institute for Health Research University College London Hospitals Biomedical Research Centre (NIHR BRC UCLH/UCL High Impact Initiative). Mattias Heinrich, Benjamin Irving, Carole Sudre, Michael Hütel, M. Jorge Cardoso, Pankaj Daga and Matthias Ehrhardt for discussions.


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Jieqing Jiao
    • 1
  • Pawel Markiewicz
    • 1
  • Ninon Burgos
    • 1
  • David Atkinson
    • 2
  • Brian Hutton
    • 3
  • Simon Arridge
    • 4
  • Sebastien Ourselin
    • 1
    • 5
  1. 1.Translational Imaging Group, CMICUniversity College LondonLondonUK
  2. 2.Centre for Medical ImagingUniversity College LondonLondonUK
  3. 3.Institute of Nuclear MedicineUniversity College LondonLondonUK
  4. 4.Centre for Medical Image ComputingUniversity College LondonLondonUK
  5. 5.Dementia Research Centre, Institute of NeurologyUniversity College LondonLondonUK

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