[Neuroimaging] [DIPY] propagator anisotropy estimation using MAP(L)MRI

[Ping-Hong Yeh]

Hi Rutger,

 Thanks for the fix.

Do have the estimate of approximate time needed for doing mcdmi_fod_fit on
a data of 240*240*187 with 1mm in resolution for total 289 volumes?

It has been running for more than 2 days on a MAC OS with 2 X 2.66 GHz
6-Core, 96GB memory machine.


Thank you.

Ping

On Sun, Apr 22, 2018 at 6:10 PM, Rutger Fick <fick.rutger at gmail.com> wrote:

> Hi Ping,
>
> Great to hear you're trying the toolbox!
>
> Thanks for pointing out the bug, I just fixed it in the repository, so you
> should be able to load the gradient directions without having the error now.
>
> Dmipy is completely general in that it can import any PGSE-based
> acquisition scheme with any number of non-diffusion weighted volumes. Dmipy
> internally normalizes the signal according to the mean of all b0-values,
> and automatically detects which measurements belong to the same acquisition
> shell.
>
> Let me know if you have any more questions or just generally what your
> experience is using dmipy :-)
>
> Best,
> Rutger
>
> On 21 April 2018 at 19:54, Ping-Hong Yeh <pinghongyeh at gmail.com> wrote:
>
>> Hi Rutger,
>>
>> The failure was caused by multiple [ 0 0 0]  arrays in the gradient table
>> that were used for acquiring non-diffusion weighted volumes. It started
>> running after I modified the gradient  table by adding 1 to the z-direction
>> of [ 0 0 0] to become [ 0 0 1].
>> Can dmipy import the gradient DWI volumes with multiple non-diffusion
>> weighted volumes interspersed in-between?
>>
>> Thank you.
>>
>> Ping
>>
>>
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>
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