Fit diffusion-weighted imaging data to a variety of models. Using the fits we compute residuals which are used in estimating noise standard deviation. The mean signal is defined as the average of the non-diffusion weighted (T2 weighted) or b=0 images. The SNR then is defined as the ratio of the signal to the noise std images. Note that the assumption is that noise is independent across voxels but "same" across directions.
Fit diffusion-weighted imaging data to a variety of models
License
AndrewJSchoen/dwifit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
About
Fit diffusion-weighted imaging data to a variety of models
Resources
License
Stars
Watchers
Forks
Releases
No releases published
Packages 0
No packages published