Quantitative and clinical analysis of SPECT image registration for epilepsy studies

Benjamin H. Brinkmann, Terence J. O'Brien, Shmuel Aharon, Michael K. O'Connor, Brian P. Mullan, Dennis P. Hanson, Richard A. Robb

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17 Citations (Scopus)


This study reports quantitative measurements of the accuracy of two popular voxel-based registration algorithms-Woods' automated image registration algorithm and mutual information correlation-and compares these with conventional surface matching (SM) registration. Methods: The registration algorithms were compared (15 different matches each) for (a) three-dimensional brain phantom images, (b) an ictal SPECT image from a patient with partial epilepsy matched to itself after modification to simulate changes in the cerebral blood flow pattern and (c) ictal/interictal SPECT images from 15 patients with partial epilepsy. Blinded visual ranking and localization of the subtraction images derived from the patient images were also performed. Results: Both voxel-based registration methods were more accurate than SM registration (P < 0.0005). Automated image registration algorithm was more accurate than mutual information correlation for the computer-simulated ictal/interictal images and the patient ictal/interictal studies (P < 0.05). The subtraction SPECTs from SM were poorer in visual ranking more often than the voxel-based methods (P < 0.05). Conclusion: Voxel intensity-based registration algorithms provide significant improvement in ictal/interictal SPECT registration accuracy and result in a clinically detectable improvement in the subtraction SPECT images.

Original languageEnglish
Pages (from-to)1098-1105
Number of pages8
JournalJournal of Nuclear Medicine
Issue number7
Publication statusPublished - 1 Jul 1999
Externally publishedYes


  • Cerebral blood flow
  • Ictal/interictal SPECT
  • Image registration
  • Partial epilepsy

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