title: Atlas-based segmentation for globus pallidus internus targeting on low-resolution MRI.
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.
authors.affiliation: AA Martinos Center for Biomedical Imaging, Dept of Radiology, MGH, Charlestown, MA, USA. iacono@nmr.mgh.harvard.edu
authors.forename: Maria I
authors.initials: MI
authors.lastname: Iacono
authors.forename: Nikos
authors.initials: N
authors.lastname: Makris
authors.forename: Luca
authors.initials: L
authors.lastname: Mainardi
authors.forename: John
authors.initials: J
authors.lastname: Gale
authors.forename: Andre
authors.initials: A
authors.lastname: van der Kouwe
authors.forename: Azma
authors.initials: A
authors.lastname: Mareyam
authors.forename: Jonathan R
authors.initials: JR
authors.lastname: Polimeni
authors.forename: Lawrence L
authors.initials: LL
authors.lastname: Wald
authors.forename: Bruce
authors.initials: B
authors.lastname: Fischl
authors.forename: Emad N
authors.initials: EN
authors.lastname: Eskandar
authors.forename: Giorgio
authors.initials: G
authors.lastname: Bonmassar
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D005917:Globus Pallidus / Q000473:pathology*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008953:Models, Anatomic; D010300:Parkinson Disease / Q000473:pathology*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique