[Neuroimaging] [DIPY] propagator anisotropy estimation using MAP(L)MRI
pinghongyeh at gmail.com
Fri Jan 12 15:48:36 EST 2018
Thanks for the prompt reply.
May I have the code for estimating PA?
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.
> 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.
>> Neuroimaging mailing list
>> Neuroimaging at python.org
> Neuroimaging mailing list
> Neuroimaging at python.org
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