Fast Tractography Streamline Search
Last updated on
Dec 9, 2021
Fast Tractography Streamline Search.
- Hierarchical search using a space partitioning tree (binary search tree / KD-tree ).
- Using an adapted distance measure (Entry-wise matrix distance).
Etienne St-Onge ( estonge in mattermost)
Brainhack Global 2021 Event
Create a repository for a Fast tractography / streamline search method.
And develop useful scripts / methods.
Link to project repository/sources
Goals for Brainhack Global
- Find an optimized space partitionning tree that can be adapted (Nanoflann).
- Adapt distances adapted for tractography streamlines (L21 entry-wise).
- Create, adapt and optimize the search function, (C++, with python “binder”).
- Discuss & choose a Library architecture / structure.
- Create usefull scripts to search streamlines within a tractogram.
- Clustering algorithms using a sparse distance matrix.
Good first issues
- issue one: Discuss about the project (how can you help with this project or learn about tractography).
- issue two: Code or improve functions to search for similar streamlines.
- issue three: Create scripts and utlity functions.
- Python : Any level (want to learn python for diffusion / tractography ?)
- Python : Intermediate (want to do streamline clustering ?)
- C++ : Intermediate (want to improve / optimize “core” functions)
What will participants learn?
How to interact with streamlines / tractography in python. (Dipy / ScilPy / Tractoflow)
Data to use
Number of collaborators
Credit to collaborators
To define !
connectome, diffusion, tractography
Things to do after the project is submitted and ready to review.