Automating neuroimaging analysis workflows with Nipype, Arcana and Banana

Analysis of neuroimaging-research data involves the sequential application of algorithms implemented in a number of heterogeneous toolkits (e.g. FSL, SPM, MRTrix, ANTs, AFNI, DiPy). The workshop will show how to wrap neuroimaging tools within consistent interfaces and link them together into robust workflows using the Nipype Python package (http://nipype.readthedocs.io). Participants will then be shown how common components of these analysis workflows can be consolidated within object-oriented base classes using the Abstraction of Repository Centric ANAlysis (Arcana) (http://arcana.readthedocs.io) framework, and how this is used in the Brain imAgiNg Analysis iN Arcana (Banana) package to capture the arcana (obscure knowledge) of neuroimaging analysis workflow design.

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Call for Characterisation Community Champions

The Characterisation Virtual Laboratory (CVL) Champions are a community of researchers, university lecturers, and bioimaging professionals taking part in a skills development program. The program is to enhance the national characterisation computing infrastructure and apply FAIR FAIR (Findable, Accessible, Interoperable, Reusable) data principles to research workflows, by upskilling scientists and bioimaging professionals for continuation of these goals.

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