Mtnormalize vs dwibiascorrect for 4D DWI

I would like to run a bias field correction on my DWI before fitting
[multi-tissue NODDI] (dmipy/example_multi_tissue_noddi.ipynb at master · AthenaEPI/dmipy · GitHub).

In the past I have used your dwibiascorrect tool, but I saw a thread that suggested correcting the DWI by dividing by the bias field output by mtnormalize (i.e., check_norm output). Would you recommend one bias field correction method over the other for 4D DWI? Would it do better for models fit specifically using gray matter and white matter tissue responses?
Thanks so much for your assistance and advice.