User:Inorton/Slicer4:DTMRI Thoughts

Background

Audiences

• Clinical/research end users: need simple, efficient, relatively intuitive workflow to generate tractography and perform selection and statistics operations.
• Pipeline users: the underlying implementations need to be abstracted sufficiently to allow creation of pipeline tools for large-study purposes.
• Clinical developers: integrate DTI functionality for domain-specific purposes (neurosurgery, neurology, etc.)
• DTI Researchers:
  • Could use Slicer+ipython+numpy+... instead of matlab and custom code. Advantages: data-reading and visualization boilerplate code already exists. Challenges: learning curve; the python suite is less integrated than matlab, but it's getting better; relative stability: matlab rarely crashes.
  • Implementation of new algorithms in Slicer opens up larger potential userbase.

Slicer advantages

See big list of DTI software here: User:inorton/DTI_Software_List.

There are several excellent DTI-centric applications. What advantages does Slicer have for DTI work?

• More user-friendly data loading: TrackVis requires command line preprocessing; MedInria and TrackVis require manual gradient entry; DTI studio is limited to ROI exploration only (as far as I know)
• Many segmentation options already available - no external tool (TrackVis, DTI Studio) or separate interface (MedInria) required.
• Already integrated with intra-operative systems via OpenIGTLink functionality
• Open-source license (TrackVis closed, MedInria non-commercial, DTI Studio closed)
• DicomToNRRDConverter test suite: test suite exists to validate DICOM loading from many different scanner types, with special emphasis on DTI private header information.

Slicer disadvantages

(this is referring to Slicer3 interactive DTMRI tools: these areas need improvement in Slicer 4)

• Current fiber data model is inefficient for interactive use on large sets (tens of thousands) of fiber tracts.
• Missing good interactive ROI selection, clustering, and editing capability for pre-computed fibersets.
• Need subset selection and coloring.
• Labelmap seeding is not multi-threaded so whole-brain tractography takes forever.
• Disjointed interface: no integrated GUI for full DICOMs->tracts->measurements workflow.

Existing NA-MIC resources

• teem: the Slicer3 interactive DTI implementation is based largely on teem through the vtkTeem libraries.
  • http://teem.sourceforge.net/
• GTRACT: command-line tools for DTI pipeline processing
  • http://www.nitrc.org/projects/vmagnotta/
  • http://wiki.slicer.org/slicerWiki/index.php/GTRACT_V4
• UNC DTI Tools (FiberViewer):
  • http://www.niral.unc.edu/
  • http://www.ia.unc.edu/dev/download/index.htm

Existing open-source external resources

See big list of DTI software here: User:inorton/DTI_Software_List

• (BSD-like licenses)
• DiPy: diffusion imaging in python. Currently pre/alpha but in active development. (BSD license)
  • http://nipy.sourceforge.net/dipy/
• DTI-query and CINCH: (BSD license)
  • http://graphics.stanford.edu/projects/dti/