2009 Winter Project Week StochasticTractography

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St helix test 01 GUI.png

Key Investigators

  • BWH: Marek Kubicki, Julien de Siebenthal


Stochastic Tractography module has the ultimate goal to offer an estimation of the probability of white matter connection between two regions of the brain. For that, connectivity map is the fundamental output of the current algorythm implementation. It reveals given two regions the distribution of probability of connection per voxel.

Approach, Plan

A complete pipeline implementation was forseen in order to give to the researcher the best access to the different features Stochastic Tractography can offer. Based on the MatLAB implementation and constantly compared to it, a Python integration was devised. It offers as a proof of concept the possibility to directly prototype an algorithm with direct integration into the Slicer solution without using MatLAB. This should alleviate issues related to code translation from MatLAB to Slicer.


The pipeline is implemented and functional. First test series show accurate adequacy between MatLAB and Python numerical computations of the Stochastic Tractography algorythm. We would like during NAMIC integrate already existing Python wrapping of the Rician and Eddy current correction filters. An ideal wrapping solution for Slicer is indeed still to be defined. Moreover, we would like also during NAMIC to find out an EPI correction filter or if needed prototype a new one.