Symmetric Diffeomorphic Image Registration: Evaluating Automated Labeling of Elderly and Neurodegenerative Cortex and Frontal Lobe

  • Brian B. Avants
  • Murray Grossman
  • James C. Gee
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4057)


One of the most challenging problems in modern neuroimaging is detailed characterization of neurodegeneration. Quantifying spatial and longitudinal atrophy patterns is an important component of this process. These spatiotemporal signals will aid in discriminating between related diseases, such as frontotemporal dementia (FTD) and Alzheimer’s disease (AD), which manifest themselves in the same at-risk population. We evaluate a novel symmetric diffeomorphic image registration method for automatically providing detailed anatomical measurement over the aged and neurodegenerative brain. Our evaluation will compare gold standard, human segmentation with our method’s atlas-based segmentation of the cerebral cortex, cerebellum and the frontal lobe. The new method compares favorably to an open-source, previously evaluated implementation of Thirion’s Demons algorithm.


Autism Spectrum Disorder Frontal Lobe Image Registration Frontotemporal Dementia Deformable Image Registration 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Brian B. Avants
    • 1
  • Murray Grossman
    • 1
  • James C. Gee
    • 1
  1. 1.Penn Image Computing and Science Laboratory (PICSL)University of PennsylvaniaPhiladelphia

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