[Neuroimaging] Analyzing the topology of ROIs and flood-filling in python (skimage?)

Thu Sep 3 06:50:42 CEST 2015

Hi Omar,

The other ROIs are here:
https://github.com/jyeatman/AFQ/tree/master/templates. I will think about
the rest of your response tomorrow!

Cheers,

Ariel

On Wed, Sep 2, 2015 at 7:39 PM, Jesus-Omar Ocegueda-Gonzalez <
jomaroceguedag at gmail.com> wrote:

> Actually, Ariel, nearest neighbor interpolation is a very unstable
> operation. If you interpolate at x or x+epsilon you may get different
> results for a very small epsilon, and discarding one single voxel may lead
> to a rejection of a large number of streamlines (I'm thinking about the
> boundary of the ROI too!, not only the "hole" ). I think it would be a more
> precise selection if you warped the streamlines to the template and select
> them there (now I see that we need that extension to the diffeomorphic map
> asap!).
>
> On Wed, Sep 2, 2015 at 9:19 PM, Jesus-Omar Ocegueda-Gonzalez <
> jomaroceguedag at gmail.com> wrote:
>
>> Thanks Ariel, and don't worry, this is very related to the work I'm doing
>> now, so this is actually very useful. I almost reproduced your experiment,
>> by any chance can you share: LOCC_ni, ROCC_ni and midsag_ni?
>>
>> On Wed, Sep 2, 2015 at 8:29 PM, Ariel Rokem <arokem at gmail.com> wrote:
>>
>>> Hi Omar,
>>>
>>> Excellent - thanks so much for taking a look! I know that you are very
>>> busy these days, and so your attention on this is highly appreciated! I
>>> will try experimenting more with this, with different input parameters, as
>>> you suggested.
>>>
>>> If you also want to take a look, since #680 and #681 were merged into
>>> dipy, you can now run:
>>>
>>>     import dipy.data as dpd
>>>     MNI_T2 = dpd.read_mni_template()
>>>
>>> To get the template data.
>>>
>>> Thanks again,
>>>
>>> Ariel
>>>
>>> On Wed, Sep 2, 2015 at 6:16 PM, Jesus-Omar Ocegueda-Gonzalez <
>>> jomaroceguedag at gmail.com> wrote:
>>>
>>>> Hello guys!,
>>>> I have been working on this issue for some days now (this is very
>>>> interesting Ariel!, thanks for sharing your findings). Satra is totally
>>>> right that **in theory** the transformations should preserve the topology.
>>>> Unfortunately, the transformations are only **approximately**
>>>> diffeomorphic. I am totally sure that this issue should be there in the
>>>> original version of ants too (dipy's implementation is the same algorithm),
>>>> although maybe the new version (antsRegistration) may have some
>>>> improvements that I'm not aware of.
>>>>
>>>> Having said that, you can make the transforms closer to diffeomorphic
>>>> by reducing the `step_length` parameter (in millimeters) from
>>>> `SymmetricDiffeomorphicRegistration`, which by default is 0.25 mm. You may
>>>> try something about 0.15 mm. The objective is to avoid making very
>>>> "aggressive" iterations, so another way to achieve this is by increasing
>>>> the smoothing parameter from the CCMetric, the parameter is `sigma_diff`,
>>>> which by default is 2.0, you may try something bout 3.0 (I would first try
>>>> reducing the step size, though).
>>>>
>>>> I would like to try some other ideas, by any chance can you share the
>>>> data (MNI_T2)?
>>>> Thank you very much!
>>>> -Omar.
>>>>
>>>>
>>>>
>>>> On Wed, Sep 2, 2015 at 7:28 PM, Satrajit Ghosh <satra at mit.edu> wrote:
>>>>
>>>>> hi ariel,
>>>>>
>>>>> can you do nearest neighbor interpolation in
>>>>> `mapping.inverse_transform`? if your original ROI doesn't have holes and
>>>>> you are doing a diffeomorphic mapping, your target shouldn't have holes
>>>>> either. for a comparison you could run antsRegister and
>>>>> antsApplyTransforms, with nearest neighbor interpolation.
>>>>>
>>>>> cheers,
>>>>>
>>>>> satra
>>>>>
>>>>> On Wed, Sep 2, 2015 at 8:13 PM, Ariel Rokem <arokem at gmail.com> wrote:
>>>>>
>>>>>> Hi everyone,
>>>>>>
>>>>>> Jason and I are working on a port of his AFQ system (
>>>>>> https://github.com/jyeatman/afq) into dipy. We've started sketching
>>>>>> out some notebooks on how that might work here:
>>>>>>
>>>>>> https://github.com/arokem/AFQ-notebooks
>>>>>>
>>>>>> The main thrust of this is in this one:
>>>>>>
>>>>>>
>>>>>> https://github.com/arokem/AFQ-notebooks/blob/master/AFQ-registration-callosum.ipynb
>>>>>>
>>>>>> The first step in this process is to take a standard ROI of some part
>>>>>> of the brain (say, corpus callosum, which is where we are starting) and
>>>>>> warp it into the subject's individual brain through a non-linear
>>>>>> registration between the individual brain and the template brain on which
>>>>>> the ROI was defined (in this case MNI152). Registration works phenomenally
>>>>>> (see cell 17), but because this is a non-linear registration, we find
>>>>>> ourselves with some holes in the ROI after the transformation (see cell 27
>>>>>> for a sum-intensity projects). We are trying to use
>>>>>> scipy.ndimage.binary_fill_holes to, well, fill these holes, but that
>>>>>> doesn't seem to be working for us (cell 35 still has that hole...).
>>>>>>
>>>>>> Any ideas about what might be going wrong? Are we using fill_holes
>>>>>> incorrectly? Any other tricks to do flood-filling in python? Should we be
>>>>>> using skimage?
>>>>>>
>>>>>> Thanks!
>>>>>>
>>>>>> Ariel
>>>>>>
>>>>>> _______________________________________________
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>>>>>>
>>>>>>
>>>>>
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>>>>>
>>>>
>>>>
>>>> --
>>>> "Cada quien es dueño de lo que calla y esclavo de lo que dice"
>>>> -Proverbio chino.
>>>> "We all are owners of what we keep silent and slaves of what we say"
>>>> -Chinese proverb.
>>>>
>>>> http://www.cimat.mx/~omar
>>>>
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>>>
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>>
>>
>> --
>> "Cada quien es dueño de lo que calla y esclavo de lo que dice"
>> -Proverbio chino.
>> "We all are owners of what we keep silent and slaves of what we say"
>> -Chinese proverb.
>>
>> http://www.cimat.mx/~omar
>>
>
>
>
> --
> "Cada quien es dueño de lo que calla y esclavo de lo que dice"
> -Proverbio chino.
> "We all are owners of what we keep silent and slaves of what we say"
> -Chinese proverb.
>
> http://www.cimat.mx/~omar
>
> _______________________________________________
> Neuroimaging mailing list
> Neuroimaging at python.org
> https://mail.python.org/mailman/listinfo/neuroimaging
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>
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