Iterative Structural and Functional Synergistic Resolution Recovery (iSFS-RR) Applied to PET-MR Images in Epilepsy

J. Silva-Rodríguez, J. Cortés, X. Rodríguez-Osorio, J. López-Urdaneta, J. Pardo-Montero, P. Aguiar, C. Tsoumpas

Research output: Contribution to journalArticleAcademicpeer-review

5 Citations (Scopus)


Structural Functional Synergistic Resolution Recovery (SFS-RR) is a technique that uses supplementary structural information from MR or CT to improve the spatial resolution of PET or SPECT images. This wavelet-based method may have a potential impact on the clinical decision-making of brain focal disorders such as refractory epilepsy, since it can produce images with better quantitative accuracy and enhanced detectability. In this work, a method for the iterative application of SFS-RR (iSFS-RR) was firstly developed and optimized in terms of convergence and input voxel size, and the corrected images were used for the diagnosis of 18 patients with refractory epilepsy. To this end, PET/MR images were clinically evaluated through visual inspection, atlas-based asymmetry indices (AIs) and SPM (Statistical Parametric Mapping) analysis, using uncorrected images and images corrected with SFS-RR and iSFS-RR. Our results showed that the sensitivity can be increased from 78% for uncorrected images, to 84% for SFS-RR and 94% for the proposed iSFS-RR. Thus, the proposed methodology has demonstrated the potential to improve the management of refractory epilepsy patients in the clinical routine.

Original languageEnglish
Pages (from-to)2434-2442
Number of pages9
JournalIEEE Transactions on Nuclear Science
Issue number5
Publication statusPublished - Oct-2016
Externally publishedYes


  • Epilepsy
  • image processing
  • partial volume correction
  • PET-MR


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