Atlas-based segmentation for globus pallidus internus targeting on low-resolution MRI
Year: 2011
Type: conference-paper
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.
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Awards: Imaging of DLPFC and amygdala impact on relative preference in cocaine addiction, Center for Functional Imaging Technologies, Intracranial Micro Magnetic Stimulation of the Frontal Eye Field in Monkeys, Identification and Validation of Human Hypothalamic Nuclei in-vivo and ex-vivo Us, High-Field MR-Compatible Dense Array EEG using Polymer Thick Film Technology
OpenAlex ID: W1966385556