Software for Diffusion MRI
This work was partially supported by the ARC Diffusion MRI. To learn more, please visit the web page http://www-sop.inria.fr/odyssee/arc2007/
The algorithms developed within the Odyssée Project team and related to the Diffusion Tensor and Q-Ball imaging are all available upon request from the INRIA source forge ( https://gforge.inria.fr ) as an extension to the Brainvisa ( http://brainvisa.info ) software platform for visualization and analysis of multi-modality brain data. One can use all the estimation and visualization tools developed at Odyssee, from DTI estimation, regularization, segmentation to Q-ball estimation, to fiber ODF estimation and tractography algorithms.
We now have users from IRISA, VISAGES, Rennes (Barillot et al), from INSERM, Paris and Universite de Montreal (H. Benali, J.C. Cohen-Adad et al), from Salpétrière Hospital, Paris (S.Lehericy, C.Delmaire, et al), from Toulouse (Landreau et al), from Eindhoven Technical University, CalTech in USA and other national and international sites.
The current library comprising geometric and variational methods developed to estimate, regularize, segment and perform tractography in DT (Diffusion Tensor) and HARDI (High Angular Resolution) MRI images was improved in two fundamental ways. In the first place, the building system was changed from Automake to CMake technologies. This improvement lead to adding support to use the library in Linux, Windows and OS X, systematize testing procedure. In the second place, the library was embedded into two open-source high level languages languages, TCL and Python.
Within the new library, new visualization schemes for Q-Ball images represented by spherical harmonic decomposition were developed. These visualization schemes based in open-source software tools, the Visualization Toolkit (VTK) and the CImg library, greatly improve the speed and Application Programming Interface (API) usability of the visualization library.
Finally taking advantage of the high level language embedding and visualization improvement, efforts are being made in order to rapidly include Q-Ball visualization and processing tools as plug-ins for the medical image processing tool Slicer3, http://www.na-mic.org/Wiki/index.php/Slicer