An accurate registration of the BigBrain dataset with the MNI PD25 and ICBM152 atlases
Autor: | Yanyu Xiao, Jonathan C. Lau, Ali R. Khan, Taylor Anderson, Terry M. Peters, D.L. Collins, Jordan DeKraker |
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Jazyk: | angličtina |
Rok vydání: | 2019 |
Předmět: |
Statistics and Probability
Data Descriptor Computer science Brain imaging Mri studies Library and Information Sciences Surgical planning Brain mapping Education 03 medical and health sciences Magnetic resonance imaging 0302 clinical medicine Neuroimaging Humans Psychology Mri brain lcsh:Science 030304 developmental biology 0303 health sciences Brain Mapping Neurosciences Brain BigBrain Magnetic Resonance Imaging Computer Science Applications Manual segmentation lcsh:Q Statistics Probability and Uncertainty Cartography Neurological disorders 030217 neurology & neurosurgery Information Systems |
Zdroj: | Scientific Data, Vol 6, Iss 1, Pp 1-9 (2019) Brain and Mind Institute Researchers' Publications Medical Biophysics Publications Scientific Data |
ISSN: | 2052-4463 |
DOI: | 10.1038/s41597-019-0217-0 |
Popis: | Brain atlases that encompass detailed anatomical or physiological features are instrumental in the research and surgical planning of various neurological conditions. Magnetic resonance imaging (MRI) has played important roles in neuro-image analysis while histological data remain crucial as a gold standard to guide and validate such analyses. With cellular-scale resolution, the BigBrain atlas offers 3D histology of a complete human brain, and is highly valuable to the research and clinical community. To bridge the insights at macro- and micro-levels, accurate mapping of BigBrain and established MRI brain atlases is necessary, but the existing registration is unsatisfactory. The described dataset includes co-registration of the BigBrain atlas to the MNI PD25 atlas and the ICBM152 2009b atlases (symmetric and asymmetric versions) in addition to manual segmentation of the basal ganglia, red nucleus, amygdala, and hippocampus for all mentioned atlases. The dataset intends to provide a bridge between insights from histological data and MRI studies in research and neurosurgical planning. The registered atlases, anatomical segmentations, and deformation matrices are available at: https://osf.io/xkqb3/. Measurement(s)neuroantomical mappingTechnology Type(s)computational modeling techniqueSample Characteristic - OrganismHomo sapiens Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.9914126 |
Databáze: | OpenAIRE |
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