Automated segmentation of basal ganglia and deep brain structures in MRI of Parkinson’s disease

  • Claire HaegelenEmail author
  • Pierrick Coupé
  • Vladimir Fonov
  • Nicolas Guizard
  • Pierre Jannin
  • Xavier Morandi
  • D. Louis Collins
Original Article



Template-based segmentation techniques have been developed to facilitate the accurate targeting of deep brain structures in patients with movement disorders. Three template-based brain MRI segmentation techniques were compared to determine the best strategy for segmenting the deep brain structures of patients with Parkinson’s disease.


T1-weighted and T2-weighted magnetic resonance (MR) image templates were created by averaging MR images of 57 patients with Parkinson’s disease. Twenty-four deep brain structures were manually segmented on the templates. To validate the template-based segmentation, 14 of the 24 deep brain structures from the templates were manually segmented on 10 MR scans of Parkinson’s patients as a gold standard. We compared the manual segmentations with three methods of automated segmentation: two registration-based approaches, automatic nonlinear image matching and anatomical labeling (ANIMAL) and symmetric image normalization (SyN), and one patch-label fusion technique. The automated labels were then compared with the manual labels using a Dice-kappa metric and center of gravity. A Friedman test was used to compare the Dice-kappa values and paired t tests for the center of gravity.


The Friedman test showed a significant difference between the three methods for both thalami (p < 0.05) and not for the subthalamic nuclei. Registration with ANIMAL was better than with SyN for the left thalamus and was better than the patch-based method for the right thalamus.


Although template-based approaches are the most used techniques to segment basal ganglia by warping onto MR images, we found that the patch-based method provided similar results and was less time-consuming. Patch-based method may be preferable for the subthalamic nucleus segmentation in patients with Parkinson’s disease.


Basal ganglia MRI template Patch-based method Parkinson’s disease Segmentation 


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Copyright information

© CARS 2012

Authors and Affiliations

  • Claire Haegelen
    • 1
    • 2
    • 3
    • 4
    • 5
    Email author
  • Pierrick Coupé
    • 1
    • 6
  • Vladimir Fonov
    • 1
  • Nicolas Guizard
    • 1
  • Pierre Jannin
    • 2
    • 3
    • 4
  • Xavier Morandi
    • 2
    • 3
    • 4
  • D. Louis Collins
    • 1
  1. 1.McConnell Brain Imaging CentreMontreal Neurological InstituteMontrealCanada
  2. 2.Faculty of Medicine, U746INSERMRennes CedexFrance
  3. 3.VisAGeS Unit/ProjectINRIARennes CedexFrance
  4. 4.UMR 06074, IRISACNRS, University of Rennes 1Rennes CedexFrance
  5. 5.Service de NeurochirurgieHôpital PontchaillouRennes Cedex 9France
  6. 6.LaBRI CNRS, UMR 5800University of BordeauxTalence CedexFrance

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