Table 1.
Diffusion MRI tractography algorithms.
| Algorithm # | Pre-Processing? | Reconstruction Technique | Software | Tractography Method | Algorithm | Seed | Miscellaneous |
|---|---|---|---|---|---|---|---|
| 1 | None | DTI | Diffusion Toolkit + Trackvis | Deterministic | FACT + Spline filtering | Seed (as ROI) | Diffusion Toolkit default parameters |
| 2 | Seed600um (as ROI) | ||||||
| 3 | Sphere ROI (r=10v) centered on Seed | ||||||
| 4 | None | Qball | Diffusion Toolkit + Trackvis | Deterministic | FACT + Spline filtering | Seed (as ROI) | Diffusion Toolkit default parameters |
| 5 | Seed600um (as ROI) | ||||||
| 6 | Sphere ROI (r=10v) centered on Seed | ||||||
| 7 | None | Ball & Sticks (bedpostx) | FSL | Probablistic | Probtrackx | Seed (as seed) | FSL Default Parameters: No FA Threshold |
| 8 | Seed600um (as seed) | ||||||
| 9 | None | DTI | DSI Studio | Deterministic | DSI Studio default tracking | Seed (as ROI) | 2000 tracks generated |
| 10 | Seed (as seed) | ||||||
| 11 | Seed600 (as ROI) | ||||||
| 12 | Seed600 (as seed) | ||||||
| 13 | Sphere ROI (r=10v) centered on seed | ||||||
| 14 | Sphere seed (r=10v) centered on seed | ||||||
| 15 | None | Qball | DSI Studio | Deterministic | DSI Studio default tracking | Seed (as ROI) | - SH order = 4 - No ODF Sharpening - 2000 tracks generated |
| 16 | Seed (as seed) | ||||||
| 17 | Seed600 (as ROI) | ||||||
| 18 | Seed600 (as seed) | ||||||
| 19 | Sphere ROI (r=10v) centered on seed | ||||||
| 20 | Sphere seed (r=10v) centered on seed | ||||||
| 21 | Response function estimated from highest FA voxels | CSD | MRTrix | Probablistic* | iFOD2 | Seed (as seed) | MRTrix3 Default Parameters - 5000 Tracks generated |
| 22 | Seed600um (as seed) | ||||||
| 23 | Seed (as ROI) | ||||||
| 24 | Seed600 (as ROI) | ||||||
| 25 | Response function estimated from iterative method | CSD | MRTrix | Probablistic* | iFOD2 | Seed (as seed) | MRTrix3 Default Parameters - 5000 Tracks generated |
| 26 | Seed600um (as seed) | ||||||
| 27 | Seed (as ROI) | ||||||
| 28 | Seed600 (as ROI) | ||||||
| 29 | None | DTI | MRTrix | Deterministic | TensorDet | Seed (as seed) | MRTrix3 Default Parameters - 5000 Tracks generated |
| 30 | Seed600um (as seed) | ||||||
| 31 | Seed (as ROI) | ||||||
| 32 | Seed600 (as ROI) | ||||||
| 33 | None | DTI | MRTrix | Probabalistic | TensorProb | Seed (as seed) | MRTrix3 Default Parameters - 5000 Tracks generated |
| 34 | Seed600um (as seed) | ||||||
| 35 | Seed (as ROI) | ||||||
| 36 | Seed600 (as ROI) | ||||||
| 37 | Response function estimated from highest FA voxels | CSD | MRTrix | Probablistic* | SIFT + iFOD2 | Seed (as ROI) | 10 million streamlines SIFTed to 1 million |
| 38 | Seed600um (as ROI) | ||||||
| 39 | Response function estimated from iterative method | CSD | MRTrix | Probablistic* | SIFT + iFOD2 | Seed (as ROI) | 10 million streamlines SIFTed to 1 million |
| 40 | Seed600 (as ROI) |
*
We note that the MRTrix iFOD2 algorithm uses samples drawn from a fiber orientation distribution to build the streamlines, and aims to reflect the anatomical distribution of fibers rather than statistical uncertainty. Thus, these are not “strictly” probabilistic, but share many similarities and are often described as probabilistic.