GitHub Repository for Imaging Data Processing and Community Collaboration

Analyzing and Reusing Data
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We’re happy to launch a new GitHub repository dedicated to the processing and analysis of imaging data, designed to streamline processing of widely used brain measures and to serve as a launchpad for novel analysis pipelines that require further validation by the community.

Repository Goals

  • Standardization & Efficiency: The repository hosts scripts and workflows for efficiently extracting the most commonly used neuroimaging metrics (structural, functional, DAT-SPECT, etc.)-making it easier for researchers to adopt best practices and ensure consistency across studies.
  • Community Collaboration: We invite all members of the data community to contribute their own scripts, workflows, and pipelines-whether fully developed or in progress-for specific analyses. This collaborative approach aims to facilitate validation, extension, and implementation of methods by other researchers.
  • Platform for Sharing and Reproducibility: By providing a shared space for code and workflow exchange, the repository will help lower the barriers to reproducibility and foster the development of robust, validated imaging analysis tools, similar to initiatives like Med-ImageTools and PyTomography, which have demonstrated the value of open-source, community-driven imaging software.

How You Can Participate:

  • Share your processing scripts or analysis pipelines, whether they are designed for standard measures or for novel, exploratory analyses.
  • Submit issues or pull requests to suggest improvements, request new features or scripts of interest, or collaborate on further expansion of existing workflows.
  • Use the repository to find validated, community-reviewed scripts for your own projects, and help validate others’ contributions by testing and providing feedback.

Why This Matters:

  • Accelerate Method Development: By pooling resources and expertise, we can accelerate the development and validation of imaging analysis methods.
  • Enhance Reproducibility: Open sharing of code and workflows supports reproducibility and transparency in imaging research.
  • Foster Innovation: Community-driven platforms have proven to be powerful engines for innovation, enabling researchers to build on each other’s work and adapt tools for new applications.

Get Started:

Please get in touch for questions, suggestions, or to get involved.

@ehutchins @hirotaka @jgottesman @bmarebwa @gginnan @cameronreidhamilton

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Thanks for starting this thread Amgad, this is great! Let’s build it up to include other modalities as well! and we can link LivingPark as well.

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We have introduced a new folder in this repository: “Imaging/DAT-SPECT at main · MJFF-ResearchCommunity/Imaging · GitHub”. This folder includes scripts and detailed instructions for calculating the striatal binding ratio (SBR) across seven distinct striatal subregions. These subregions are delineated according to cortico-striatal connectivity patterns, with each voxel assigned to the cortical zone-limbic, executive, rostral-motor, caudal-motor, parietal, occipital, or temporal-to which it has the highest probability of connection. For further details, see: Atlases/striatumconn
and: https://bktimes.net/data/board_notice/1655444268-39.pdf

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This looks great! Thank you for sharing this with the community - it’s very helpful.

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I am always interested in this area but not an expert. This is great and will definitely try it out. Are you considering a docker image or something similar to help set-up the environment in the future?

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Thanks for sharing! What a great resource.

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