Difference between revisions of "2012 Project Week:BatchProcessing"
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| − | + | * Satra and Hans resolved a number of issues and are now processing multi-hundred dataset studies (building on fixes from Chris) | |
| + | * HD Processing scripts can be example for others integrating slicer modules with other neuroimaging tools with data in XNAT | ||
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** Need to resolve dependencies | ** Need to resolve dependencies | ||
** Optionally require users to install independent version of scipy | ** Optionally require users to install independent version of scipy | ||
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Latest revision as of 21:27, 12 January 2012
Home < 2012 Project Week:BatchProcessing
Key Investigators
- MIT: Satra Ghosh
- Iowa: Hans Johnson
- Kitware: Jean-Christophe Fillion-Robin
- BWH: Andrey Fedorov
- Isomics: Steve Pieper
Various DBP projects and other users have requested the ability to automate large tasks and interoperate with other image analysis tools. Nipype is a solution that is proving useful in this domain so we would like to further refine it as an option to the na-mic community.
Objective
Batch processing with Slicer and Nipype
Approach, Plan
- Work on HD use cases to improve batch processing framework
- Develop example workflows as templates for other projects
- Identify and if possible fix any issues that prevent smooth integration of slicer modules into batch workflows.
Progress
- Satra and Hans resolved a number of issues and are now processing multi-hundred dataset studies (building on fixes from Chris)
- HD Processing scripts can be example for others integrating slicer modules with other neuroimaging tools with data in XNAT
- This project drove a wide discussion about further leveraging python code in slicer (ipython, ScipPy, PyXNAT, etc)
Delivery Mechanism
- Possibly nipype as an extension.
- Need to resolve dependencies
- Optionally require users to install independent version of scipy
