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

Conference Paper


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
  •   Raniga, Parnesh (external author)
  •   Villemagne, Victor L. (external author)
  •   Rowe, Christopher C. (external author)
  •   Fripp, Jurgen

Publication Date


  • 2012

Citation


  • Zhou, L., Salvado, O., Dore, V., Bourgeat, P., Raniga, P., Villemagne, V. L., Rowe, C. C. & Fripp, J. (2012). MR-less surface-based amyloid estimation by subject-specific atlas selection and Bayesian fusion. In N. Ayache, H. Delingette, P. Golland & K. Mori (Eds.), International Conference on Medical Image Computing and Computer-Assisted Intervention (pp. 220-227). Berlin, Germany: Springer-Verlag.

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers1/1271

Start Page


  • 220

End Page


  • 227

Place Of Publication


  • Berlin, Germany

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
  •   Raniga, Parnesh (external author)
  •   Villemagne, Victor L. (external author)
  •   Rowe, Christopher C. (external author)
  •   Fripp, Jurgen

Publication Date


  • 2012

Citation


  • Zhou, L., Salvado, O., Dore, V., Bourgeat, P., Raniga, P., Villemagne, V. L., Rowe, C. C. & Fripp, J. (2012). MR-less surface-based amyloid estimation by subject-specific atlas selection and Bayesian fusion. In N. Ayache, H. Delingette, P. Golland & K. Mori (Eds.), International Conference on Medical Image Computing and Computer-Assisted Intervention (pp. 220-227). Berlin, Germany: Springer-Verlag.

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers1/1271

Start Page


  • 220

End Page


  • 227

Place Of Publication


  • Berlin, Germany