[Neuroimaging] [dipy] Import csd model precomputed by mrtrix

Fri May 27 11:44:06 EDT 2016

Hi again,

On Fri, May 27, 2016 at 5:23 AM, Ariel Rokem <arokem at gmail.com> wrote:

> Hi Paolo,
>
> Thanks for the update. Sorry to hear it didn't work as hoped.
>
> On Fri, May 27, 2016 at 2:07 AM, Paolo Avesani <avesani at fbk.eu> wrote:
>
>> Thanks for your replies.
>> A brief update.
>>
>> Samuel is right. I have in mind to manage the multi-shell model from
>> mrtrix3.
>> It is clear that up to now it is not viable until the work in progress
>> from Bago becomes available.
>>
>> I tried to follow the example suggested by Ariel, focusing on a single
>> shell csd model (coming from dwi2fod command of mrtrix3),
>> and setting the sphere as the one used by mrtrix3 (a 300 points). The
>> "predict" method raised an issue of disalignment of matrix size.
>>
>> The issue is at line 217 of csdecon.py when a product between
>> "predict_matrix" and "sh_coeff" takes place.
>> The "predict matrix" has size (90,45): 90 volumes, 45 sh
>> The "sh_coeff" has size (145, 174, 145, 45): the xyz dimensions of the
>> volume, 45 sh
>>
>> It looks the size of predict matrix is wrong. It should be
>> (145,174,145,90).
>>
>>
>>
> Or the predict_matrix should be (45, 90)? Would be useful if you shared a
> minimal example that raises this error.
>

I was wrong, of course. Does Bago's fix (
https://github.com/nipy/dipy/pull/1062) resolve this for you?

Cheers,

Ariel

> Cheers,
>
> Ariel
>
>
>
>>
>>
>> On Thu, May 26, 2016 at 4:07 AM, Samuel St-Jean <stjeansam at gmail.com>
>> wrote:
>>
>>> Indeed, I thought I read the multitissue version was used here, my
>>> mistake as the question does not directly imply that.
>>>
>>> The regular single shell hopefully does the same (at least I can
>>> personally attest the mrtrix2 version and dipy version give similar fodf up
>>> to a small rounding factor, but that was before the cholesky decomposition
>>> step, so now they should behave the same).
>>> On May 26, 2016 09:37, "Bago" <mrbago at gmail.com> wrote:
>>>
>>>> Samuel mrtrix has at least two models implemented. The multi-shell
>>>> (multi-tissue) model cannot be used with single shell data and the original
>>>> CSD model cannot be used with multi-shell data.
>>>>
>>>> Bago
>>>>
>>>> On Wed, May 25, 2016 at 5:13 PM Samuel St-Jean <stjeansam at gmail.com>
>>>> wrote:
>>>>
>>>>> Their wiki explains it, a sqrt(2) to normalize is used in mrtrix3, so
>>>>> multiplying your coefficients with that and using the mrtrix2 functions
>>>>> should do it.
>>>>>
>>>>> Although dipy only does single shell, so conclude with consideration
>>>>> that the algorithm is different from mrtrix3. Also, csd is a bad signal
>>>>> predictor (but good for angle estimation), see the sparc dmri challenge
>>>>> paper for example.
>>>>> On May 26, 2016 07:55, "Ariel Rokem" <arokem at gmail.com> wrote:
>>>>>
>>>>>>
>>>>>>
>>>>>> On Wed, May 25, 2016 at 4:41 PM, Bago <mrbago at gmail.com> wrote:
>>>>>>
>>>>>>> I believe they did change their basis (please correct me if I'm
>>>>>>> wrong but I believe they went from a non-normalized SH basis to a
>>>>>>> normalized SH basis).
>>>>>>>
>>>>>>>
>>>>>> So they have the same basis as dipy now, but the coefficients appear
>>>>>> in a different order? That should make life even easier!
>>>>>>
>>>>>>
>>>>>>> Also projecting onto a sphere is one way to _estimate_ the
>>>>>>> coefficients in a different basis. The cleaner way is to just re-order the
>>>>>>> coefficients and apply the appropriate scaling. If both basis are
>>>>>>> normalized (which dipy is) the scaling should be 1 or -1.
>>>>>>>
>>>>>>>
>>>>>> Fair point, but to be just a little bit facetious: given enough
>>>>>> points on the sphere and knowledge of the target maximal order of the
>>>>>> coefficients, wouldn't estimating be the same as transforming? Works for
>>>>>> the FFT, I believe :-)
>>>>>>
>>>>>> Bago
>>>>>>>
>>>>>>> On Wed, May 25, 2016 at 3:31 PM Ariel Rokem <arokem at gmail.com>
>>>>>>> wrote:
>>>>>>>
>>>>>>>> On Wed, May 25, 2016 at 1:09 PM, Bago <mrbago at gmail.com> wrote:
>>>>>>>>
>>>>>>>>> Hi Paolo,
>>>>>>>>>   mrtrix and dipy define the SH basis slightly differently, so the
>>>>>>>>> precomputed FOD values need to be adjusted if you want to skip the fit step
>>>>>>>>> and initialize the Fit object directly. IRC we don't currently have the
>>>>>>>>> code to do that, but it would be something we'd like to incorporate.
>>>>>>>>>
>>>>>>>>> Did they change their basis set when they transitioned to mrtrix3?
>>>>>>>> We do have these functions:
>>>>>>>>
>>>>>>>>
>>>>>>>> https://github.com/nipy/dipy/blob/master/dipy/reconst/shm.py#L852-L923
>>>>>>>>
>>>>>>>> That should work with the previous version of mrtrix (mrtrix2?).
>>>>>>>> You can use these to transform between coefficient sets:
>>>>>>>>
>>>>>>>>     sf = sh_to_sf(mrtrix_coeffs, sphere, sh_order,
>>>>>>>> basis_type='mrtrix')
>>>>>>>>     dipy_coeffs = sf_to_sh(sf, sphere, sh_order, basis_type=None) #
>>>>>>>> This defaults to the dipy basis set
>>>>>>>>
>>>>>>>> and then use the CSD model object to predict:
>>>>>>>>
>>>>>>>>     from dipy.reconst.csdeconv import
>>>>>>>>  ConstrainedSphericalDeconvModel
>>>>>>>>     csd_model = ConstrainedSphericalDeconvModel(gtab, response,
>>>>>>>> sh_order=sh_order) # Note: you still need to calculate the response
>>>>>>>> function!
>>>>>>>>     pred_signal = csd_model.predict(dipy_coeffs, gtab, S0)
>>>>>>>>
>>>>>>>> I think that something like this should work (but I haven't tried
>>>>>>>> it myself).
>>>>>>>>
>>>>>>>>
>>>>>>>>> I have a WIP version of the multi-shell CSD model on a separate
>>>>>>>>> branch, I plan on merging it but wasn't intending to get to that for a few
>>>>>>>>> months. If you'd like to look at before then I can push the branch up to
>>>>>>>>> github.
>>>>>>>>>
>>>>>>>>> Sounds interesting! I'd love to see what you have so far!
>>>>>>>>
>>>>>>>> Cheers,
>>>>>>>>
>>>>>>>> Ariel
>>>>>>>>
>>>>>>>>
>>>>>>>>> Bago
>>>>>>>>>
>>>>>>>>> On Wed, May 25, 2016 at 2:31 AM Paolo Avesani <avesani at fbk.eu>
>>>>>>>>> wrote:
>>>>>>>>>
>>>>>>>>>> I would like to take advantage of the "predict" method of
>>>>>>>>>> reconstruction models in dipy. The goal is to assess the quality of results.
>>>>>>>>>>
>>>>>>>>>> I have already computed the reconstruction models using mrtrix3
>>>>>>>>>> and stored the ODF files. For this reason I would need to initialize the
>>>>>>>>>> csd model by importing the data from ODF stored by mrtrix3.
>>>>>>>>>>
>>>>>>>>>> The questions are manifold:
>>>>>>>>>> - may I initialize the csd model by providing the precomputed
>>>>>>>>>> values and skipping the "fit" step?
>>>>>>>>>> - may I import the value of precomputed model from a file stored
>>>>>>>>>> by mrtrix3?
>>>>>>>>>> - is the csd model in dipy compliant with the output of
>>>>>>>>>> multi-shell csd model computed by mrtrix3?
>>>>>>>>>>
>>>>>>>>>> I hope my questions and my goal is formulated clearly.
>>>>>>>>>> Thanks for your support.
>>>>>>>>>> Paolo
>>>>>>>>>>
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>>>>>>>>>
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>>
>>
>> --
>> -------------------------------------------------------
>> Paolo Avesani
>> Fondazione Bruno Kessler
>> via Sommarive 18,
>> 38050 Povo (TN) - I
>> phone:   +39 0461 314336
>> fax:        +39 0461 302040
>> email:     avesani at fbk.eu
>> web:       avesani.fbk.eu
>>
>>
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