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).
Read MoreA combined symposium to plan how we enable interoperability and collaboration between researchers in a data-driven world.
Read MoreThe 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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