Application of the anatomical fiducials framework to a clinical dataset of patients with Parkinson's disease.

ABSTRACT: Establishing spatial correspondence between subject and template images is necessary in neuroimaging research and clinical applications such as brain mapping and stereotactic neurosurgery. Our anatomical fiducial (AFID) framework has recently been validated to serve as a quantitative measure of image registration based on salient anatomical features. In this study, we sought to apply the AFIDs protocol to the clinic, focusing on structural magnetic resonance images obtained from patients with Parkinson's disease (PD). We confirmed AFIDs could be placed to millimetric accuracy in the PD dataset with results comparable to those in normal control subjects. We evaluated subject-to-template registration using this framework by aligning the clinical scans to standard template space using a robus

SUBMITTER: Abbass M 

PROVIDER: S-EPMC8741686 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature