Functional and structural synergy for resolution recovery and partial volume correction in brain PET

Miho Shidahara, Charalampos Tsoumpas, Alexander Hammers, Nicolas Boussion, Dimitris Visvikis, Tetsuya Suhara, Iwao Kanno, Federico E. Turkheimer

Research output: Contribution to journalArticlepeer-review

73 Citations (Scopus)


Purpose: Positron Emission Tomography (PET) has the unique capability of measuring brain function but its clinical potential is affected by low resolution and lack of morphological detail. Here we propose and evaluate a wavelet synergistic approach that combines functional and structural information from a number of sources (CT, MRI and anatomical probabilistic atlases) for the accurate quantitative recovery of radioactivity concentration in PET images. When the method is combined with anatomical probabilistic atlases, the outcome is a functional volume corrected for partial volume effects. Methods: The proposed method is based on the multiresolution property of the wavelet transform. First, the target PET image and the corresponding anatomical image (CT/MRI/atlas-based segmented MRI) are decomposed into several resolution elements. Secondly, high-resolution components of the PET image are replaced, in part, with those of the anatomical image after appropriate scaling. The amount of structural input is weighted by the relative high frequency signal content of the two modalities. The method was validated on a digital Zubal phantom and clinical data to evaluate its quantitative potential. Results: Simulation studies showed the expected relationship between functional recovery and the amount of correct structural detail provided, with perfect recovery achieved when true images were used as anatomical reference. The use of T1-MRI images brought significant improvements in PET image resolution. However improvements were maximized when atlas-based segmented images as anatomical references were used; these results were replicated in clinical data sets. Conclusion: The synergistic use of functional and structural data, and the incorporation of anatomical probabilistic information in particular, generates morphologically corrected PET images of exquisite quality.

Original languageEnglish
Pages (from-to)340-348
Number of pages9
Issue number2
Publication statusPublished - 2009 Jan 15
Externally publishedYes


  • Fusion
  • Multi-modality
  • PET-CT
  • Partial volume correction
  • Positron emission tomography
  • Resolution recovery
  • Synergistic
  • Wavelet transform

ASJC Scopus subject areas

  • Neurology
  • Cognitive Neuroscience


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