GSoC Project Idea 7: Implementing automatic white matter parcellation in Nighres



Nighres is an open-source Python package for processing of high-resolution neuroimaging data (github, documentation, publication). It began as a Google summer of code project (development blog) with the aim of making the Java based advanced image processing algorithms of CBS High-Res Brain Processing Tools and IMCN available to to a wider community. Nighres provides user-friendly Python interfaces for these tools, documents them through concrete examples and facilitates integration with other popular Python-based Neuroimaging tools such as Nibabel, Nilearn and Nipype. Many new tools have been added in the recent release 1.1.0 and the community of users is growing.

A particular functionality that we would like to add to Nighres is a fully automated method to extract white matter tracts from diffusion MRI tensors, based on a Markov random field model and anatomical priors (publication). This method was originally implemented in Java. During this year’s Google summer of Code project we would like to achieve the following:

  • re-implement the method efficiently in Python
  • implement a Nighres interface for the algorithm
  • create documentation and an example workflow
  • potentially extend the method to more advance diffusion MRI models (so far it is optimized and tested for tensors)

Skills: The student should be proficient in Python and have a background in MR image processing, in particular diffusion weighted MRI. Familiarity with other Python-based Neuroimaging tools and experience would be advantageous.

Mentors: Julia M Huntenburg (Nighres core developer,, Champalimaud, Lisbon, Portugal. Pierre-Louis Bazin (Nighres core developer, creator of the white matter parcellation method, MPI CBS, Leipzig, Germany.