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Strange @arnaudbore, if you look this link https://pypi.org/project/dipy/#files dipy 1.1.1 is present for many OS

What is your environment ?

Hi there, I have questions about the usage of the word “reconstruction” in dipy’s documentation. e.g. for tensor model, the tutorial’s title is “Reconstruction of the diffusion signal with the Tensor model“. Is it really “reconstruction”? Or it’s some “modeling”. Because I saw in MRI field, reconstruction usually refers to reconstruct the MR image from k-space data, but here we actually already have the images, which makes me confused.

@arokem Hi. I'm trying to apply pyAFQ in these days. I do not apply it using the cli, but I use directly some of the defined functions. In my case I have available the tractogram coregistered to MNI space, but not the DWI data, and I m trying to apply only AFQ segmentation to the tractogram. Now, because of the lack of the dwi I m calling the function Segmentation.segment by providing reg_tamplate, img_affine, and mapping where reg_template is MNI152_T1_1mm, img_affine is the affine of this mni_t1, and mapping is the indentity mapping (since tractogram and template are already in the same space). After this premise I explain the problem: The segmentation seems to work in the first step, waypoints rois filtering, but it produces a strange behaviour in the second step, endpoints filtering, where some tracts like ATR have a huge drop in terms of number of streamlines. I looked into detail on the reason of this drop, by saving the endpoints AAL rois corresponding to the ATR_L, and I overlap it with the segmentation produced by AFQ without endpoints filtering.

here what I obtain: the endpoint roi is in the wrong hemisphere.

@pietroastolfi : thanks for reporting. Could you please post an issue on the pyAFQ repo: https://github.com/yeatmanlab/pyAFQ/issues ?

That's a great find and might be related to things that others have seen: yeatmanlab/pyAFQ#235

My main conclusion is that this part of the processing is not yet robust enough. Works sometimes, but not bullet proof yet

So, we need to investigate

@tecork : I believe the examples here: https://dipy.org/documentation/1.1.1./examples_built/affine_registration_3d/#example-affine-registration-3d

should work in 2d as well

If not, in a pinch I might try adding a singleton dimension to your data just to get it in there

from dipy.tracking.local import LocalTracking, ThresholdTissueClassifier

the error : No module named 'dipy.tracking.local'

from dipy.tracking.local_tracking import LocalTracking

According to the api documentation https://dipy.org/documentation/1.1.0./api_changes/ , ThresholdTissueClassifier -> ThresholdStoppingCriterion

Posted a question on GitHub (dipy/dipy#2164) but I'll throw it here for visibility too. Ran DKI reconstruction and got some weird outputs. The DTI scalars look ok but the DKI scalars don't resemble white matter paths. Any help would be great.

Hi everyone, I am moving over from ANTsPy to Dipy and was wondering how I can apply a diffeomorphic transform to points after the registration is done. That is, I am looking for a function that takes a set of points and a registration transformation as input and outputs the transformed points moved along the velocity field of the transform, like ants.apply_transforms_to_points in the AntsPy package. Many thanks for any help!

Hi @Garyfallidis , how are you doing? A question to the guru: once I perform clustering with QuickBundles, how do I get access to the streamline that is the closest to the centroid in its cluster? In my application, I cannot simply take the resulting centroid, as it has a lower number of points. Any help would be appreciated! ;-)

In general, once I obtain a cluster, I'd like to extract the streamline (from the input set, i.e., exactly the same geometry, nb of points etc) that best represents the cluster. We implemented a way, by recomputing the distance of each streamline from the centroid, but I was wondering whether there was a more direct way from the output of QuickBundles. For instance, without the need to recompute the distances

Good morning.hope everyone is fine.I have a small problem.. I would like to minimize the test_function. basically, test_function() takes 3 variables - m, n and p. The goal is to find such values of these 3 variables that the function returns the minimal possible value.I am using nelder-mead minimization problem. while running my script for x0 = [25.0, 45.0, 10.0] i am getting error like Maximum number of function evaluations has been exceeded. Anyway I followed the stackoverflow link to write my code. https://stackoverflow.com/questions/55751317/minimize-multivariable-function please help me on this.Thanks.My data and script is attached here https://i.fluffy.cc/HLR1jCJLLV8lX4NfjSqbjRKG6DsB4bwS.html stackoverflow link is blocked in my area.

Hi. I'm new to dipy and would like to set up an analysis pipeline using the free water elimination model. As I'm working through the preprocessing examples, I did not find information for motion and geometric correction. This will be an important step for me. Can you point me in the right direction? Should I use another tool to generate motion/eddy current - corrected data first? Thanks.

Hi @CherylMcC I'd suggest trying QSIPrep: https://qsiprep.readthedocs.io/en/latest/. It will do both of these corrections with a single interpolation

Hi all, I'm trying to save generated streamlines using StatefulTractogram but get the error message below. Also, I'm able to save tractograms from raw and eddy corrected images. However, I am getting this problem after distortion correction using ANTs. But, the streamlines are generated and can be visualized with the fury package for raw, eddy and distortion+eddy correction. Any help would be greatly appreciated. Thanks.

ValueError Traceback (most recent call last)

<ipython-input-33-25d7d840788d> in <module>()

36 from dipy.io.streamline import save_trk

37

---> 38 sft = StatefulTractogram(streamlines, img, Space.RASMM)

39 #save_trk(sft, "DTItractogram_deterministic_ctxwm-lh-postcentral_T1space-disteddy.trk")

40

~/miniconda3/envs/ants/lib/python3.6/site-packages/dipy/io/stateful_tractogram.py in **init**(self, streamlines, reference, space, origin, data_per_point, data_per_streamline)

119 'using them with StatefulTractogram.')

120 else:

--> 121 space_attributes = get_reference_info(reference)

122 if space_attributes is None:

123 raise TypeError('Reference MUST be one of the following:\n'

~/miniconda3/envs/ants/lib/python3.6/site-packages/dipy/io/utils.py in get_reference_info(reference)

276

277 if not affine[0:3, 0:3].any():

--> 278 raise ValueError('Invalid affine, contains only zeros.'

279 'Cannot determine voxel order from transformation')

280 voxel_order = ''.join(nib.aff2axcodes(affine))

ValueError: Invalid affine, contains only zeros.Cannot determine voxel order from transformation

Hi all, I need to run SIFT2 ( https://mrtrix.readthedocs.io/en/latest/reference/commands/tcksift2.html) using the fod computed with dipy, but I have doubts on the compatibility of the two e.g., https://community.mrtrix.org/t/first-spherical-harmonic-coefficient-y-0-0-meaning/507 . Is there some of you that already experienced such situation?

Hi @gamorosino, you can do eddy current correction by affinely registering all non-b0 volumes to the b0. We are planning to have a tutorial and interface about that. For the moment, you can look at the example from @Garyfallidis and add an extra step with our diffeomorphic registration: https://gist.github.com/Garyfallidis/42dd1ab04371272050221275c6ab9bd6

Hello all,

I have a question about the Symmetric Diffeomorphic Registration in 3D tutorial. I would like to view/save the mapping that transforms the moving image into the static image. I have tried using get_map() but this gives an error : DiffeomorphicMap' object has no attribute 'static_to_ref'. Any suggestions on how to obtain the mapping data?

I have a question about the Symmetric Diffeomorphic Registration in 3D tutorial. I would like to view/save the mapping that transforms the moving image into the static image. I have tried using get_map() but this gives an error : DiffeomorphicMap' object has no attribute 'static_to_ref'. Any suggestions on how to obtain the mapping data?

Hi @ejb119 ! The mapping object that get_map() returns is created in the optimize() method, so get_map() can only be used after running the optimize() method. I was able to reproduce the issue with

```
from dipy.align.imwarp import SymmetricDiffeomorphicRegistration
from dipy.align.metrics import EMMetric
metric = EMMetric(3)
sdr = SymmetricDiffeomorphicRegistration(metric, level_iters=[10, 10, 5])
mapping = sdr.get_map()
```

Also, the same mapping object is returned by the optimize() method as well.

`mapping = sdr.optimize(static, moving)`

For visualizing the deformation map, you can look at the 2D example: https://dipy.org/documentation/1.1.1./examples_built/syn_registration_2d