An introduction to working with magnetic resonance imaging (MRI) data in Python.
This lesson teaches:
- a (re?) introduction to MR nomenclature - with BIDS
- how neuroimaging data is stored
- "converting" your data to BIDS
- BIDS apps
- queueing up neuroimaging pipelines
| # | Episode | Time | Question(s) |
|---|---|---|---|
| 1 | Before we start | 30 | What is Python and why should I learn it? |
| 2 | From the scanner to our computer | 30 | What are the main MRI modalities? What's the first step necessary to start working with MRI data? |
| 3 | Anatomy of a NIfTI | 25 | How are MRI data represented digitally? |
| 4 | Data organization with BIDS | 45 | |
| 5 | Exploring open MRI datasets | 45 | How does standardizing neuroimaging data ease the data exploration process |
| 6 | BIDS derivatives | 45 |
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Please see the current list of issues for ideas for contributing to this
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nicely explained in the chapter Contributing to a Project in Pro Git
by Scott Chacon.
Look for the tag 
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A list of contributors to the lesson can be found in AUTHORS
Instructional material from this lesson is made available under the Creative Commons Attribution (CC BY 4.0) license. Except where otherwise noted, example programs and software included as part of this lesson are made available under the MIT license. For more information, see LICENSE.
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