Automatic Trajectory Planning of DBS Neurosurgery from Multi-modal MRI Datasets

  • Silvain Bériault
  • Fahd Al Subaie
  • Kelvin Mok
  • Abbas F. Sadikot
  • G. Bruce Pike
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6891)


We propose an automated method for preoperative trajectory planning of deep brain stimulation image-guided neurosurgery. Our framework integrates multi-modal MRI analysis (T1w, SWI, TOF-MRA) to determine an optimal trajectory to DBS targets (subthalamic nuclei and globus pallidus interna) while avoiding critical brain structures for prevention of hemorrhages, loss of function and other complications. Results show that our method is well suited to aggregate many surgical constraints and allows the analysis of thousands of trajectories in less than 1/10th of the time for manual planning. Finally, a qualitative evaluation of computed trajectories resulted in the identification of potential new constraints, which are not addressed in the current literature, to better mimic the decision-making of the neurosurgeon during DBS planning.


Deep brain stimulation Parkinson’s disease image-guided neurosurgery automatic planning 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Silvain Bériault
    • 1
  • Fahd Al Subaie
    • 1
  • Kelvin Mok
    • 1
  • Abbas F. Sadikot
    • 1
  • G. Bruce Pike
    • 1
  1. 1.McConnell Brain Imaging CentreMontreal Neurological InstituteMontrealCanada

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