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Reconstruction FOD #1044
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Yes. You can do that by replacing these lines: https://github.com/nipy/dipy/blob/master/doc/examples/reconst_csd.py#L25-L30 with lines that assign your simulated signal into You will also need to have a response function, instead of the response function estimated here: https://github.com/nipy/dipy/blob/master/doc/examples/reconst_csd.py#L48 But if you simulated this yourself, you should know what the values for that are, because they correspond to the values used in each tensor element in the signal that was generated by your simulation. |
Thank you very much for the quick reply. |
I think this means you want to set:
Where S0 is the mean non-diffusion weighted signal used to generate the simulation. |
Hi, |
Is this question answered? Can we close? |
yes you can close this discussion.Thank you very much.
Le mercredi 4 octobre 2017 à 20:20:06 UTC+1, Jean-Christophe Houde <notifications@github.com> a écrit :
Is this question answered? Can we close?
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Hi,
I'm Ines BEN ALAYA , i'm a PhD student and i'm working with diffusion MRI.
I intend to estimate the FOD from a signal that has been generated using a multi-tensor model ,i download the file reconst_csd.py.
Can i reconstrutct the FOD using the diffusion signal and the response function (i don't have the diffusion weighted images).
I will be grateful if you can help me.
Best regards.
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