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Abstract #3229

Comparing Two Atlas-Based Automatic Segmentation Methods for Subthalamic Nucleus Deep Brain Stimulation

Y. Xiao1, L. Bailey1, M. Mallar Chakravarty2, S. Beriault1, A. F. Sadikot3, G. Bruce Pike1, D. Louis Collins1

1McConnell Brain Imaging Centre, Montral Neurological Institute, McGill University, Montral, Qubec, Canada; 2Kimel Family Translational Imaging-Genetic Laboratory, Research Imaging Centre, Centre for Addiction, Toronto, Canada; 3Division of Neurosurgery, McGill University, Montral, Canada

Accurate automated segmentation of the subthalamic nucleus (STN) and its surrounding structures can help improve planning for deep brain stimulation procedures when treating Parkinsons disease. Two atlas-based automatic segmentation methods, one with histologically defined atlas, and the other with in vivo T2w-image-defined atlas, were compared for the segmentation of the STN, red nucleus, and substantia nigra, by using the manual segmentation on the consensus of T2*w image and R2* map acquired on a 3T scanner as the ground truth. Although they both provided acceptable results, the in vivo T2w-image-defined atlas performed better on average.