Lestropie
commented
2 weeks ago Animation below shows raw data, then denoising using eigenspectrum truncation, then optimal shrinkage.
@dchristiaens @jdtournier Would appreciate some input on the optimal shrinkage implementation:
- To make sure that my implementation is correct (some of the variable handling was already different to that in published manuscript)
- Given that the noise level threshold is determined based on choosing a specific component index, we want to make sure that the truncation / alignment of the optimal shrinkage function relative to that selection is correct; ie. check for off-by-one errors.
Not familiar with what may be considered to be best practise here, but I at least have a basic sense of the concept.
Depending on where the upper threshold of the MP distribution is determined to be relative to the component eigenvalues, inclusion of components in the output DWI series could be fractional.