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Update DKI, WMTI, fwDTI examples and give more evidence to WMTI and fwDTI models #1944

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merged 4 commits into from Aug 1, 2019

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@RafaelNH
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commented Jul 31, 2019

Hi! In this PR, I am submitting a documentation update of the following models fwDTI, DKI, and WMTI.

Basically I've improved the following aspects.

  • Add the Rescience paper that reports all the code adaptions done for fwDTI implementation in Dipy (we were still citing the previous implementation proposed by Hoy et al.)
  • Splitting the DKI example - this to address issue #1774.
  • Give more highlight to WMTI and fwDTI models in Dipy's gallery. Previously, these models were added as a subsection of DTI and DKI models, which might be decreasing WMTI and fwDTI visibility.

PS: This is my last PR for Dipy's release 1.0

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Thank you @RafaelNH! Apart from some typos, it seems ready to go. I just need to run this example and generate the documentation to be sure there is no rendering problem.

obtain invariant rotational measures not limited to well-aligned fiber
populations [NetoHe2015]_.
heterogeneity [Jensen2010]_. Moreover, DKI can be used to: 1) derive concrete
biophysical parameters, such as the density of axonal fibres and diffusion

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typo: fibers

well-aligned fibers). Following Fieremans et al. [Fieremans2011]_, a simple way
to select this region is to generate a well-aligned fiber mask based on the
values of diffusion sphericity, planarity and linearity. Here we will follow
these selection criteria for a better comparision of our figures with the

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typo: comparison

@skoudoro skoudoro added this to the 1.0 milestone Jul 31, 2019

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commented Jul 31, 2019

@skoudoro - done!

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commented Aug 1, 2019

Can you have a look at this one @arokem? I suppose it is ready to go but can you confirm?

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I had a few small suggestions

microstructural models to DT and KT estimated from DKI. For instance,
Fieremans et al. [Fierem2011]_ showed that DKI can be used to
estimate the contribution of hindered and restricted diffusion for well-aligned
fibers - model that was later referred to as the white matter tract integrity

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fibers - model that was later referred to as the white matter tract integrity
fibers - a model that was later referred to as the white matter tract integrity
these latter measures can be used to distinguish processes of axonal loss from
processes of myelin degeneration.
In this example, we show how to process a diffusion weighting dataset using

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In this example, we show how to process a diffusion weighting dataset using
In this example, we show how to process a dMRI dataset using

"""
As the standard DKI, WMTI requires multi-shell data, i.e. data acquired from
more than one non-zero b-value. Here, we use fetch to download a multi-shell

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more than one non-zero b-value. Here, we use fetch to download a multi-shell
more than one non-zero b-value. Here, we use a fetcher to download a multi-shell
affine = img.affine

"""
For comparison, this dataset is pre-processing using the same steps used in the

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For comparison, this dataset is pre-processing using the same steps used in the
For comparison, this dataset is pre-processed using the same steps used in the
In this example, we show how to process a diffusion weighting dataset using
an adapted version of the free water elimination proposed by [Hoy2014]_.
The full details of Dipy's free water DTI implementation was published on

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The full details of Dipy's free water DTI implementation was published on
The full details of Dipy's free water DTI implementation was published in
an adapted version of the free water elimination proposed by [Hoy2014]_.
The full details of Dipy's free water DTI implementation was published on
the ReScience C initiative [Henriques2017]_. Please cite this work if you use

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the ReScience C initiative [Henriques2017]_. Please cite this work if you use
[Henriques2017]_. Please cite this work if you use
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commented Aug 1, 2019

Looks like I can commit my suggested changes into this branch. Let me try doing this and then @RafaelNH can give us a shout (or make more commits) if any of my changes distorts his intended meaning.

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commented Aug 1, 2019

No, I stand corrected: I can't commit these changes, because I don't have permissions on @RafaelNH's fork. We'll have to wait for him to take a look and approve them.

OTOH, nothing here is crucial, so if this is holding you back, feel free to merge this now, and put an issue to remind us to do another pass of copy editing before 1.1

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commented Aug 1, 2019

Thank you for your quick answer, I think I will go ahead and make this modification on my last PR #1932

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commented Aug 1, 2019

Good plan. In that case, it's ready to go!

@arokem arokem merged commit ac3980f into nipy:master Aug 1, 2019

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commented Aug 1, 2019

I added it to your checklist in #1932 😅

@skoudoro skoudoro referenced this pull request Aug 1, 2019
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