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Question about user defined parallel diffusivity parameter in AMICO NODDI model #114
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Hello @CallowBrainProject , Best. |
Hi guys, I have an idea but it must be tested. For example, the fitting can be done by using many different parallel diffusivities (one by one). The optimal diffusivity should be the one producing a smaller residual (a better fitting to the data). This way, a different diffusivity per voxel could be used. However, this is going to increase the computation time linearly with the number of diffusivities. Anyway, this is something we may explore in the future, as this could solve the more important theoretical limitation of NODDI. What do you think? All the best, Erick |
Great,
Thank you very much for letting me know. That is indeed what I was looking
for.
Daniel
On Mon, Jun 7, 2021 at 2:58 AM Mario Ocampo ***@***.***> wrote:
Hello @CallowBrainProject <https://github.com/CallowBrainProject> ,
Yes, as it was commented in #97
<#97>, you can modify the
parameters to suit your needs.
The diffusivity parameters are dPar and dIso and can be modified with the
function set().
Let us know if this does what you wanted.
Best.
Mario
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*Daniel Callow*
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Hello, several recent studies have suggested that the standard parallel diffusivity parameter in NODDI for intraneurite diffusion (1.7) is suboptimal for measuring gray and even white matter in some samples (https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0217118 and https://www.nature.com/articles/s41598-019-48671-7).
Is there a way to alter the diffusivity parameters of our model in AMICO for the NODDI model? Thank you for any suggestions you can provide.
Daniel
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