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This is a living resource on best practices in neuroimaging analysis for the Imaging Processing Lab (LPI) at the D'Or Institute for Research and Education. The handbook is rendered on the web here, and is currently under development.
The handbook is intended to be a practical, hands-on guide for running an MRI analysis and a repository for related content. The handbook can't cover every use-case or experiment, so we focus on the most typical use-cases.
Contributions in any form (pull requests, issues, content requests/ideas) are always welcome! If you notice any irregularities in the handbook, please us know by raising an issue. You can find the recommended workflow for contributing here.
You might have never used GitHub and the whole thing might seem overwhelming. No worries, please check out the following links to learn how to use GitHub for this handbook and also your own projects!
The pages use Markdown to format the text. Check out here how to use it:
CC-BY-SA: You are free to
- share - copy and redistribute the material in any medium or format
- adapt - remix, transform, and build upon the material for any purpose, even commercially
under the following terms:
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Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
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ShareAlike — If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original.
This handbook is collaboratively authored by members of the LPI and associated labs at IDOR. The structure of this handbook borrows heavily from the Princeton Handbook for Reproducible Neuroimaging, which was based on the DataLad Handbook.