An ontologically consistent MRI-based atlas of the mouse diencephalon
In topological terms, the diencephalon lies between the hypothalamus and the midbrain. It is made up of three segments, prosomere 1 (pretectum), prosomere 2 (thalamus), and prosomere 3 (the prethalamus). A number of MRI-based atlases of different parts of the mouse brain have already been published,...
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Published in | NeuroImage (Orlando, Fla.) Vol. 157; pp. 275 - 287 |
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Main Authors | , , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
Elsevier Inc
15.08.2017
Elsevier Limited Elsevier |
Subjects | |
Online Access | Get full text |
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Summary: | In topological terms, the diencephalon lies between the hypothalamus and the midbrain. It is made up of three segments, prosomere 1 (pretectum), prosomere 2 (thalamus), and prosomere 3 (the prethalamus). A number of MRI-based atlases of different parts of the mouse brain have already been published, but none of them displays the segments the diencephalon and their component nuclei. In this study we present a new volumetric atlas identifying 89 structures in the diencephalon of the male C57BL/6J 12 week mouse. This atlas is based on an average of MR scans of 18 mouse brains imaged with a 16.4T scanner. This atlas is available for download at www.imaging.org.au/AMBMC. Additionally, we have created an FSL package to enable nonlinear registration of novel data sets to the AMBMC model and subsequent automatic segmentation.
•A detailed atlas of high resolution images of the diencephalon of the C57Bl/6J mouse.•The atlas is based on data from an average of 18 brains imaged with a 16.4T MR scanner.•The MRI atlas is the first to employ a modern developmental ontology of the diencephalon.•This atlas is available for download at www.imaging.org.au/AMBMC.•We offer an FSL package to enable nonlinear registration of novel data sets to our model. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 1053-8119 1095-9572 |
DOI: | 10.1016/j.neuroimage.2017.05.057 |