> Adam Messinger, Benjamin Jung, Jakob Seidlitz, Paul Taylor, Daniel Glen <
Description
> A collection of volumetric templates of the rhesus macaque created by nonlinear averaging of T1-weighted anatomical MRIs from multiple adult monkeys. Surface files are included. The NMT 2.0 provides increased flexibility in macaque group analysis by providing symmetric and asymmetric templates. Both templates are available with an expanded, full head field of view. The templates are available in both AC-PC orientation and in Horsley-Clarke stereotaxic orientation. Updates to the templates include: an improved mapping of the D99 atlas, improved brain masking and normalization, and files that are defined in a common template space (NMT space), using the short data type for improved storage efficiency. <
Documentation
> TBD<
Link
> TBD <
Language
> Volumetric files are in NIFTI (.nii) format, while surface files are in GIFTI (.gii) format. Alignment and brainmasking scripts (@animal_warper) are packaged with AFNI. Processing script rely on ANTs and shell scripting. <
Publication
> TBD <
Communication
> Through the GitHub repo or via email to Dr. Adam Messinger: Adam.Messinger@nih.gov <
Restrictions
> Usage requires citation of this article: TBD <
Category
> template, atlas <
[ ] Do NOT include this resource in periodic mailings about new resources on PRIME-RE
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Resource info table
Instructions
Please fill out the table above as completely as possible, i.e. replace the complete str
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with your information. Then submit it as a new issue and tag the issue with all applicable (yellow) categorical tags to specify what type of resource you are contributing. We will use this table and these tags to add your resource to the main list.Name
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Description
Tell the community what it is that your resource does. Keep it concise (a few lines).
Documentation
Does your resource include instructions on how to use it, and if so, where? This can be a hyperlink, or you can simply state that it can be found through the main link (e.g., because it's in a GitHub ReadMe.md). Jupyter Notebooks or richly annotated scripts would be great, but any documentation would be great.
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