A practical, hands on guide to the logic and practice of digital white matter segmentation
This resource is a collection of jupyer notebooks notebooks designed to build intuitions for and provide training in digital white matter segmentation. The modern-day practice of digital white matter segmentation is as much about programming as it is about neuroanatomy, which is why the medium of jupyer notebooks has been chosen. In this way, users are able to view commented code alongside text explaining the context, goals, and implications of what is being done. However, there's a catch to this! Because interactivity is key to many of these lessons, you will often need to click the rocket-ship symbol at the top of the page to open a binder. This will allow you to actually run and interact with code in your browser which, in turn, will give you a better understanding of how the code is operating.
On the left hand side of this page there is a navigation bar listing several chapters and their sub-sections. The first of these is the "Front matter" which concerns many of the formalities associated with this lesson collection. Among its sections is the chapter summaries there you'll find brief descriptions of all of the chapters covered in this guide. If you want to get a healthy dose of context and overarching themes check out the Building Bridges chapter. On the other hand, if you want to jump to the lessons, begin with Introduction to discretized image representation and maps
This is inherently a community resource, and we welcome comments and contributions. If you wish to make a comment or suggest an edit please feel free to click the GitHub symbol at the top of any page. Alternatively, feel free to reach out via email to Dan Bullock at either iisdanbul@gmail.com or dnbulloc@iu.edu.
Currently, this resource is under construction and always moving towards improvements. As such, expect the addition of new chapters and additional polish in the coming months.