Paula Andrea Martinez
Paula Andrea Martinez National Training Coordinator - Characterisation Community

Automating neuroimaging analysis workflows with Nipype, Arcana and Banana - Materials

Automating neuroimaging analysis workflows with Nipype, Arcana and Banana - Materials

Last updated 19 November 2019

Hands-on workshop Date: 15 November, 2019 (after the VBIC Annual Network Meeting) Duration: 1 day (9:30 - 5:00) Proposed Location: Melbourne, Swinburne University Advanced Technologies Centre Instructor: Thomas Close from Monash Biomedical Imaging

Automating neuroimaging analysis workflows with Nipype, Arcana and Banana

Analysis of neuroimaging-research data uses many software tools (e.g. FSL, SPM, MRTrix, ANTs, AFNI, DiPy). This makes constructing complete workflows challenging as it requires not only the relevant scientific knowledge but also familiarity with the syntax and options of each of the tools involved.

This workshop shows how to wrap neuroimaging tools within consistent interfaces and link them together into robust workflows using the Nipype Python package.

In the last part of the course, participants will learn how to extend and customise the classes in Banana to the specific needs of their own analysis, and apply these workflows to project data stored in BIDS datasets. Then finally, how workflows can be automated for data stored in XNAT repositories by encapsulating them within Docker containers and using XNAT’s “container service”.

Materials

All the materials and instructions to run the code are provided https://nbviewer.jupyter.org/github/MonashBI/nipype_arcana_workshop/blob/master/program.ipynb

Pre-requisites

  • Proficiency in Python programming, or programming in general and familiarity with object-oriented concepts.
  • A conceptual understanding of container technology (i.e. Docker/Singularity) would be beneficial.
  • Some familiarity with the function of standard neuroimaging toolkits (e.g. FSL, SPM, MRTrix, ANTs, AFNI, DiPy) would be good but not strictly necessary.
  • An account on CVL@MASSIVE is the recommended.

CVL@MASSIVE projects

If you are or want to become a new user to CVL@MASSIVE we would like to encourage you to apply for a new project or join an existing one to continue using the CVL.

  • If you are a principal investigator or a project manager please send a project request to MASSIVE by filling out the following form

https://forms.gle/GUktMZPKUHLsMGNT8. You will get a response in about 3 working days.

  • If you are a student or research assistant you need your supervisor or manager to get a project first, they can then give you the project code to join.

For further details on how to do this, please refer to https://www.cvl.org.au/cvl-desktop/cvl-accounts. This page contains account, project and password information. It is important to notice that all members of a project have read permission on it.

Next event

We are planning to run this workshop in Sydney (2020), if you know of anyone who would be interested, please get in touch.

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Characterisation Virtual Laboratory (CVL)

The CVL is a nationally funded software infrastructure collaboration to make scientific tools for image analysis and processing, available freely and cloud-ready. The CVL is also a community who support training and best data management practices.

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