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

Ping-Hong Yeh pinghongyeh at gmail.com
Fri Jan 12 15:48:36 EST 2018


Hi Roger,

Thanks for the prompt reply.
May I have the code for estimating PA?

Ping

On Jan 12, 2018 3:21 PM, "Rutger Fick" <fick.rutger at gmail.com> wrote:

> Hi Ping,
>
> MAPL is just a name for using laplacian-regularized MAP-MRI. If you're
> using the dipy mapmri implementation then you're using MAPL by default.
> From a fitted mapmri model you can estimate overall non-gaussianity using
> fitted_model.ng(), and parallel and perpendicular non-Gaussianity using
> ng_parallel() and ng_perpendicperpendicularular().
> Propagator Anisotropic is not included in the current dipy implementation.
> However, I do have a personal version of dipy's mapmri implementation that
> includes it, if you're interested.
>
> Best,
> Rutger
>
> On 12 January 2018 at 16:49, Ping-Hong Yeh <pinghongyeh at gmail.com> wrote:
>
>> Hi DIPY users,
>>
>> I would like to know the way of estimating non-Gaussian and PA,
>> mentioned in the Avram et al. “Clinical feasibility of using mean
>> apparent propagator (MAP) MRI to characterize brain tissue microstructure”
>> paper,  using MAPMRI or MAPL model.
>>
>> Thank you.
>>
>> Ping
>>
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>>
>
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