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  • Dec 06 22:46
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Eleftherios Garyfallidis
@Garyfallidis
Yes, should be resolved in a few days. We have applied for the SSL certificate.
Jean-Christophe Houde
@jchoude
:thumbsup:
Fang-Cheng Yeh
@FangChengYeh_twitter
Congratulations to the new DIPY and Website. It looks awesome!
Eleftherios Garyfallidis
@Garyfallidis
Thank you @FangChengYeh_twitter and all for your help all these years.
Fang-Cheng Yeh
@FangChengYeh_twitter
You are welcome. Wish I could help more if I knew how to code in python.
Eleftherios Garyfallidis
@Garyfallidis
Never late! :D
nis02002
@nis02002
Anyone please let me know how to load dataset from HCP with DIPY?
Eleftherios Garyfallidis
@Garyfallidis
Do you have the nifti images @nis02002 ? Can you try dipy_info?
Eleftherios Garyfallidis
@Garyfallidis
Eleftherios Garyfallidis
@Garyfallidis
alt
AlexBadea
@portokalh
I wonder if the dipy CSA implementation supports multiple b values. Many thanks!
Romulus
@romainviard
Hi all, could someone give me an hand ?
see that: import dipy
print(dipy.version) >>>> 1.0.0 It's ok but
import dipy.viz import window, actor >>>>Gives an error, I just wondering why ?
File "<ipython-input-61-930dc3d62dde>", line 6
import dipy.viz import window, actor
^
SyntaxError: invalid syntax
Eleftherios Garyfallidis
@Garyfallidis
@portokalh it will give reasonable result. Like an average ODF from the different shells. Make sure the shells are all spherical.
@romainviard from dipy.viz import window, actor
Romulus
@romainviard
@Garyfallidis Sorry I made an mistake when I wrote on gitter..."from dipy.viz import window, actor " didn't work on dipy1.0.0 (python 3) but works on dipy 0.14.0 (python 2.7), Do you confirm that it should work with the last version of dipy ? Thanks you
Eleftherios Garyfallidis
@Garyfallidis
Have you installed fury?
pip install fury
And yes it should work. I do confirm.
AlexBadea
@portokalh
thanks much @Garyfallidis !
Romulus
@romainviard
thanks @Garyfallidis you were right!!
Davis Bennett
@d-v-b
what would need to be done for registration in dipy to support masked images
Davis Bennett
@d-v-b
looks like adding properties to MutualInformationMetric
Romulus
@romainviard
Hi dipy's folks,
I'm using the great function dipy.stats.analysis.afq_profile…
And I 'm wondering two things :
  • Is it better to compute the profile on the full track/bundle (so multiple fibers) or on only one fiber (a cluster obtained using QuickBundles for example)?
  • If I want to do stats on different profiles (for example mean FA on the same tract for various subjects), how would you advice to correct statistics(multiple comparison, and espacially spacial correlation,) with Random Field Theory or another one ? In pratical with python and scipy ?
    Thanks a lot in advance,
nis02002
@nis02002
Anyone know does DIPY can do diffusion compartment imaging study?
Eleftherios Garyfallidis
@Garyfallidis
Hi @romainviard !
nis02002
@nis02002
DCI (diffusion compartment imaing) is more advanced than DTI
Eleftherios Garyfallidis
@Garyfallidis
@romainviard let me introduce you to @BramshQamar that is working on extending our statistical analysis framework and she can explain all the details to you. In short, we have a strategy for you to start with and happy to collaborate in trying new ideas.
nis02002
@nis02002
Or any other tool could implement compartment study will be great, thanks a lot
Eleftherios Garyfallidis
@Garyfallidis
@nis02002 do you have DCI data?
nis02002
@nis02002
i only have diffusion image data
i wonder can I fit the data into diffusion compartment model
nis02002
@nis02002
How can we calcuate the diffusion tensor D using tersor model?
like Apparent diffusion coefficnet?
Ariel Rokem
@arokem
@romainviard : regarding afq_profile, probably better to include multiple streamlines, rather than the centroid of a cluster (if that's what you meant)
albayenes
@albayenes
@nis02002 You can find information to calculate diffusion tensor in this tutorial https://dipy.org/documentation/1.0.0./examples_built/reconst_dti/#example-reconst-dti
There is also a function which is named as apparent_diffusion_coef(q_form, sphere) to calculate ADC in DT model
Tristan MOREAU
@Tristan2Tzara_twitter
Thank you for this great new version of dipy ! Good job :-) I have a basic question on how can we use fury to plot the spherical deconvolution results. I used the Tractoflow pipeline to preprocess my clinical data set. Using scil_compute_fodf.py with spherical harmorics basis set to 'descoteaux07' and order set to 8. I got a file 'fodf.nii.gz' of shape (133, 161, 144, 45). My question is how can I use fury to plot the fodf on coronal plan using the fodf file ? Best regards, sincerely. Tristan :-)
Ariel Rokem
@arokem
@Tristan2Tzara_twitter : check out the odf_slicer in this example: https://dipy.org/documentation/1.0.0./examples_built/reconst_csd/
Davis Bennett
@d-v-b
Can anyone point to literature / examples of dealing with masked data in a multiresolution framework?
(for registration)
the right approach seems to be to mask the data before generating the scale space, but i'm not sure
Eleftherios Garyfallidis
@Garyfallidis
Makes sense @d-v-b first mask the brain then multires. With nonlinear registration you really have to do that. There should be something about that at Arno Klein's registration comparison paper.
Davis Bennett
@d-v-b
cool, thanks
i'm looking at this in the context of nipy/dipy#1969
Davis Bennett
@d-v-b
this might be out of scope w.r.t. masking for image registration, but I notice that a lot of these registration functions / methods take 4 arguments at a minimum -- moving, fixed, moving_grid2world, fixed_grid2world -- and there are a lot of nearly duplicated code blocks which perform some operation on moving, then the same operation on fixed. Is there any appetite to simplifying this with some lightweight OOP? e.g. an object that has a data property, a mask property, and a grid2world property would save a lot of LOC in the registration codebase
this is looking pretty hairy to me:
image.png
Eleftherios Garyfallidis
@Garyfallidis
Yes @skoudoro has a plan to make this more OOP. Let's sync together.
Eleftherios Garyfallidis
@Garyfallidis
I would say more than oop the plan is to simplify some things in the reg API. Not sure yet we can take out these parameters completely at first stage. You may feel this is hairy now but after a while you see that it is quite useful. Also do look into dipy.workflows.align there we have a higher level api. Do you have a suggestion for how to reduce the number of parameters? Be happy to suggest ideas. We are good listeners :)