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MR-less surface-based amyloid estimation by subject-specific atlas selection and Bayesian fusion

Journal Article


Abstract


  • For clinical evaluation, assessing amyloid deposition with PiB-PET is desirable without requiring MR acquisition and associated fusion/segmentation techniques. A useful clinical tool is to estimate PiB-PET against the brain surface, which is however challenging using PET alone because of the lack of structural information. We propose a method to generate such estimate, where multiple atlases are selected and combined with local weights in a Bayesian framework. Qualitative and quantitative comparison with and without MRI are presented. Using PET only, the average error on the brain surface was around 13% compared to MRI-dependant method.

Authors


  •   Zhou, Luping
  •   Salvado, Oliver (external author)
  •   Dore, Vincent (external author)
  •   Bourgeat, Pierrick (external author)
  •   Raniga, Parnesh (external author)
  •   Villemagne, Victor L. (external author)
  •   Rowe, Christopher C. (external author)
  •   Fripp, Jurgen (external author)

Publication Date


  • 2012

Citation


  • Zhou, L., Salvado, O., Dore, V., Bourgeat, P., Raniga, P., Villemagne, V., Rowe, C. & Fripp, J. (2012). MR-less surface-based amyloid estimation by subject-specific atlas selection and Bayesian fusion. Lecture Notes in Computer Science, 7511 (N/A), 220-227.

Scopus Eid


  • 2-s2.0-84872902937

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/522

Number Of Pages


  • 7

Start Page


  • 220

End Page


  • 227

Volume


  • 7511

Issue


  • N/A

Abstract


  • For clinical evaluation, assessing amyloid deposition with PiB-PET is desirable without requiring MR acquisition and associated fusion/segmentation techniques. A useful clinical tool is to estimate PiB-PET against the brain surface, which is however challenging using PET alone because of the lack of structural information. We propose a method to generate such estimate, where multiple atlases are selected and combined with local weights in a Bayesian framework. Qualitative and quantitative comparison with and without MRI are presented. Using PET only, the average error on the brain surface was around 13% compared to MRI-dependant method.

Authors


  •   Zhou, Luping
  •   Salvado, Oliver (external author)
  •   Dore, Vincent (external author)
  •   Bourgeat, Pierrick (external author)
  •   Raniga, Parnesh (external author)
  •   Villemagne, Victor L. (external author)
  •   Rowe, Christopher C. (external author)
  •   Fripp, Jurgen (external author)

Publication Date


  • 2012

Citation


  • Zhou, L., Salvado, O., Dore, V., Bourgeat, P., Raniga, P., Villemagne, V., Rowe, C. & Fripp, J. (2012). MR-less surface-based amyloid estimation by subject-specific atlas selection and Bayesian fusion. Lecture Notes in Computer Science, 7511 (N/A), 220-227.

Scopus Eid


  • 2-s2.0-84872902937

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/522

Number Of Pages


  • 7

Start Page


  • 220

End Page


  • 227

Volume


  • 7511

Issue


  • N/A