Tabinda Sarwar, Kotagiri Ramamohanarao and Andrew Zalesky. Mapping connectomes with diffusion MRI: deterministic or probabilistic tractography? Magnetic Resonance in Medicine 2019;81:1368–1384
The study evaluated the state-of-the-art tractography algorithms using simulated diffusion-weighted magnetic resonance imaging (dMRI) dataset. The details of simulation can be in paper "https://onlinelibrary.wiley.com/doi/10.1002/mrm.27471" The provided scripts (main script: "demo.m") can be used to generate spherical phantom with 60 nodes. Node parcellation scheme (atlas.nii.gz) for mapping connetcome is also provided. The dataset provided is simulated with b-value=2000 s/mm2 and provided gradients scheme ("grad.m"). Details for other parameters can be found in the paper.
A dataset of 5 spherical phantoms can be found in folder "Data". The parcellation and diffusion-weighted gradients along with the masks are also included. One test phantom, with only one fiber connetcing a pair of region is also available. This could be used as a reference to deal with flipping (in case) caused by tractography algorithms.