Frequently Asked Questions  

What is TrackVis?
TrackVis is a software that can visualize and analyze fiber tracks created from MR images by Diffusion Tensor Imaging (DTI), Diffusion Spectrum Image (DSI) and other diffusion imaging techniques.

TrackVis, Diffusion Toolkit... What is the difference? Why are they separate?
TrackVis is a fiber track visualization and analysis program. It does NOT perform actual fiber tracking. Diffusion Toolkit is a set of tools that reconstruct diffusion imaging data and generate fiber track data for TrackVis to visualize. Because these two sets of tools were developed and maintained separately and each has distinguished funtionalities, we decide to distribute them as two separate programs for the ease of maintainance and upgrade. You do need both of them to perform complete diffusion data processing and analysis. Both softwares can be downloaded from this website.

Is TrackVis free?
TrackVis is freely available for academic/research/non-commercial use. To use it for other purpose, please contact us.

On what platform can I run TrackVis?
TrackVis and Diffusion Toolkit are cross-platform software. They can run on Windows XP, Mac OS X as well as Linux. Please refer to System Requirements for more details.

Where to ask questions or report bugs on Diffusion Toolkit and TrackVis?
First of all you should check FAQ section to see if the questions have been covered. If not, please go to Forum section to post questions and bug reports.

How to cite Diffusion Toolkit and TrackVis?
You may use acknowlegement like "Ruopeng Wang, Van J. Wedeen,, Martinos Center for Biomedical Imaging, Massachusetts General Hospital" or cite the related ISMRM abstract Proc. Intl. Soc. Mag. Reson. Med. 15 (2007) 3720 (view pdf).

What data format do TrackVis and Diffusion Toolkit support?
TrackVis works with Track File created by Diffusion Toolkit. Diffusion Toolkit processes raw DICOM, Nifti format and ANALYZE images.

What reconstruction/fiber tracking methods are used in Diffusion Toolkit?
* For diffusion tensor estimation, it uses linear least-squares fitting method.
* For Q-Ball/Hardi reconstruction, it uses the Spherical Harmonic Basis method by Hess CP, Mukherjee P and co. (PubMed abstract)
* For DTI fiber tracking, it uses the standard FACT by Mori S and co. (PubMed abstract) as the default method. Other alternate methods include 2nd-order Runge-Kutta, fixed step-length streamline propagation and Tensor Deflection by Lazar M, Weinstein DM and co. (PubMed abstract)
* For DSI/Q-Ball/Hardi fiber tracking, it uses FACT-alike algorithm but is based on the data model that each voxel has multiple principle diffusion directions.

Can Diffusion Toolkit do image distortion correction?
No. Diffusion Toolkit does not include tools for distortion correction. If needed, users will need to use external tools, such as FLIRT in FSL package, to do distortion correction. Diffusion Toolkit can take the corrected images in Nifti format and perform reconstruction and fiber tracking.

Can TrackVis display Tensor or ODF glyphs?
Not YET. Future version of TrackVis will support display of Tensor and ODF glyphs.

Why do I get funny looking "nonsense" tracks?
First, you should make sure the correct image orientation information was used for reconstruction. Secondly, different manufacturers may interpret image orientation differently. That is exactly why "Orientation patch" was introduced in Diffusion Toolkit. Please refer here for more information. From our limited experience, Siemens data usually do not need any orientation patches, while GE and Philips data often need to apply "Invert Y".

Why do I get broken or even empty tracks?
Diffusion Toolkit uses two types of threshold as stopping criterion for fiber tracking. One is image mask, the other is angle. So when you get broken tracks, given your data has decent quality and SNR, it should be either the mask threshold was set too high, or the angle threshold was set too low. If you get near "empty" tracks, it is very likely because the program failed to automatically find mask threshold and set the mask threshold too high. In that case, you should look at the mask image and set the threshold manually.