CUDA Diffusion Modelling Toolbox

CUDA Diffusion Modelling Toolbox (cuDIMOT)

CUDIMOT is a toolbox, part of FSL (FMRIB Software Library), for designing and implementing MRI nonlinear models on Graphics Processing Units (GPUs).

You can easily implement your diffusion MRI nonlinear model and analyse your data 200x faster using GPUs. Share your model with other users.

Download cuDIMOT NODDI (Watson) model implementation on GPUs

The toolbox includes:

  • An easy C interface for specifying your model parameters and functions.
  • Three nonlinear optimisation routines:
    • MCMC
    • Levenberg-Marquardt
    • Grid Search
  • Can use different models concatenating outputs/inputs
  • Gaussian and Rician noise modelling
  • Parameters bounds and Priors: Gaussian, Gamma, ARD, sin()
  • Bayesian information criterion (BIC) and Akaike information criterion (AIC)
  • Several diffusion MRI models implemented: Ball&Sticks, NODDI-Watson, NODDI-Bingham, Ball&Rackets
  • Can use multiple GPUs to fit a dataset

The only required libraries are FSL (FMRIB Software Library) and CUDA toolkit.
You will need an NVIDIA GPU.

Read here how to use the tool for implementing your own model.


 If you use cuDIMOT in publications, please cite:

Hernandez-Fernandez M., Reguly I., Jbabdi S, Giles M, Smith S., Sotiropoulos S.N. "Using GPUs to accelerate computational diffusion MRI: From microstructure estimation to tractography and connectomes." NeuroImage 188 (2019): 598-615.