AUTHOR=Garyfallidis Eleftherios , Brett Matthew , Amirbekian Bagrat , Rokem Ariel , Van Der Walt Stefan , Descoteaux Maxime , Nimmo-Smith Ian 

TITLE=Dipy, a library for the analysis of diffusion MRI data

JOURNAL=Frontiers in Neuroinformatics

VOLUME=Volume 8 - 2014

YEAR=2014

URL=https://www.frontiersin.org/journals/neuroinformatics/articles/10.3389/fninf.2014.00008

DOI=10.3389/fninf.2014.00008

ISSN=1662-5196

ABSTRACT=Diffusion Imaging in Python (Dipy) is a free and open source software project<br/>for the analysis of data from diffusion magnetic resonance imaging (dMRI)<br/>experiments. dMRI is an application of MRI that can be used to measure<br/>structural features of brain white matter.  Many methods have been developed to<br/>use dMRI data to model the local configuration of white matter nerve fiber<br/>bundles and infer the trajectory of bundles connecting different parts of the<br/>brain.<br/><br/>Dipy gathers implementations of many different methods in dMRI, including:<br/>diffusion signal pre-processing; reconstruction of diffusion distributions in<br/>individual voxels; fiber tractography and fiber track post-processing, analysis<br/>and visualization. Dipy aims to provide transparent implementations for<br/>all the different steps of dMRI analysis with a uniform programming interface.<br/>We have implemented classical signal reconstruction techniques, such as the<br/>diffusion tensor model and deterministic fiber tractography. In addition,<br/>cutting edge novel reconstruction techniques are implemented, such as<br/>constrained spherical deconvolution and diffusion spectrum imaging with<br/>deconvolution, as well as methods for probabilistic tracking and original<br/>methods for tractography clustering. Many additional utility functions are<br/>provided to calculate various statistics, informative visualizations, as well<br/>as file-handling routines to assist in the development and use of novel<br/>techniques.<br/><br/>In contrast to many other scientific software projects, Dipy is not being<br/>developed by a single research group. Rather, it is an open project that<br/>encourages contributions from any scientist/developer through GitHub and open<br/>discussions on the project mailing list. Consequently, Dipy today has an<br/>international team of contributors, spanning seven different academic institutions<br/>in five countries and three continents, which is still growing.