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

Rutger Fick fick.rutger at gmail.com
Fri Jan 12 15:21:12 EST 2018


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
>
> _______________________________________________
> Neuroimaging mailing list
> Neuroimaging at python.org
> https://mail.python.org/mailman/listinfo/neuroimaging
>
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mail.python.org/pipermail/neuroimaging/attachments/20180112/03493f32/attachment.html>


More information about the Neuroimaging mailing list