Atlas-based segmentation for globus pallidus internus targeting on low-resolution MRI

Annu Int Conf IEEE Eng Med Biol Soc. 2011;2011:5706-9. doi: 10.1109/IEMBS.2011.6091381.

Abstract

In this paper we report a method to automatically segment the internal part of globus pallidus (GPi) on the pre-operative low-resolution magnetic resonance images (MRIs) of patients affected by Parkinson's disease. Herein we used an ultra-high resolution human brain dataset as electronic atlas of reference on which we segmented the GPi. First, we registered the ultra-high resolution dataset on the low-resolution dataset using a landmarks-based rigid registration. Then an affine and a non-rigid surface-based registration guided by the structures that surround the target was applied in order to propagate the labels of the GPi on the low-resolution un-segmented dataset and to accurately outline the target. The mapping of the atlas on the low-resolution MRI provided a highly accurate anatomical detail that can be useful for localizing the target.

MeSH terms

  • Algorithms*
  • Computer Simulation
  • Globus Pallidus / pathology*
  • Humans
  • Image Enhancement / methods
  • Image Interpretation, Computer-Assisted / methods*
  • Models, Anatomic*
  • Parkinson Disease / pathology*
  • Pattern Recognition, Automated / methods*
  • Reproducibility of Results
  • Sensitivity and Specificity
  • Subtraction Technique*