Mailman 3 December 2019 - DIPY

[DIPY] FWDTI and DTI recon questions including if default output is upper or lower triangle
by dr.ajay.kurani＠gmail.com 24 May '20

24 May '20

Hi DIPY Experts, I am interested in saving the diffusion tensor as a NIFTI file created as part of the free water implementation. I ran the following commands: import sys import os import bz2file import numpy as np import nibabel as nib import dipy.reconst.fwdti as fwdti import dipy.reconst.dti as dti import matplotlib.pyplot as plt fdwi="dwi_tpl_max2000.nii.gz" fbval="dwi_tpl_max2000.bvals" fbvec="dwi_tpl_max2000.bvecs" mask_wb="mask.tpl.final.nii.gz" img = nib.load(fdwi) data = img.get_data() affine = img.affine mask = nib.load(mask_wb) maskdata = mask.get_data() fwdtimodel = fwdti.FreeWaterTensorModel(gtab,fit_method='NLS') fwdtifit = fwdtimodel.fit(data, mask=maskdata) 1) The following errors were displayed even though the code ran after running the fwidtifit command above: .../python_local/scipy/optimize/minpack.py:447: RuntimeWarning: Number of calls to function has reached maxfev = 1800. warnings.warn(errors[info][0], RuntimeWarning) ...python_local/dipy/reconst/fwdti.py:454: RuntimeWarning: overflow encountered in exp y = (1-f) * np.exp(np.dot(design_matrix, tensor[:7])) + \ I wanted to verify if this is just due to imperfect masking near the edge or if this means the code did not fully run and that there are errors to fix. 2) I ran the following code to save the tensor, as from my understanding fwdtifit uses the DTI tensorfit module: img = nib.Nifti1Image(fwdtifit.quadratic_form, affine) nib.save(img, 'FWms_quadratic_form.nii.gz') Is this the upper or lower triangle? The NIFTI standard is lower triangle, but given that in the DTI module has a lower_triangular function I am guessing DIPY default is the upper triangle. I am having trouble using the lower_triangular function so if you can send me the correct way to interface with this command that would be much appreciated. Thanks, Ajay

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Affine issue with atlas of 80 Bundles in MNI space
by Giulia Berto' 19 Mar '20

19 Mar '20

Hi, I am trying to use the atlas of 80 bundles you distribute here https://figshare.com/articles/Advanced_Atlas_of_80_Bundles_in_MNI_space/737… <https://figshare.com/articles/Advanced_Atlas_of_80_Bundles_in_MNI_space/737…>, but I am encountering some issues. It is written that the files are in MNI space ICBM 2009a, which has affine equal to array([[ 1., 0., 0., -98.], [ 0., 1., 0., -134.], [ 0., 0., 1., -72.], [ 0., 0., 0., 1.]]) However, all the trk files have affine equal to the identity matrix. Is there a reason why you stored in the header of the trk files the identity matrix? This for example prevents their correct visualization in TrackVis. [image: ifof_r_dipy_trackvis.png] Another question: the file whole_brain_MNI.trk, besides having the same issue with the affine, has 144678 streamlines. Is it the same whole brain tractogram Yeh is referring to in their paper? In that paper they obtained a tractogram of 550000 streamlines. Or is it maybe the union of the 80 bundles? Thank you a lot for your help, best regards, Giulia -- -- Le informazioni contenute nella presente comunicazione sono di natura privata e come tali sono da considerarsi riservate ed indirizzate esclusivamente ai destinatari indicati e per le finalità strettamente legate al relativo contenuto. Se avete ricevuto questo messaggio per errore, vi preghiamo di eliminarlo e di inviare una comunicazione all’indirizzo e-mail del mittente. -- The information transmitted is intended only for the person or entity to which it is addressed and may contain confidential and/or privileged material. If you received this in error, please contact the sender and delete the material.

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DIPY IVIM does not work correctly
by Maurizio Bergamino 17 Mar '20

17 Mar '20

Hello, I am using DIPY for the first time because I would like to analyze IVIM data. I created my python script and I ran the fit for my data. However, the results are not, in my opinion, correct. I analyzed only one slice, because the script needs time, and I wanted to be sure that it worked correctly. However, for the f index, I have 3/4 of the brain with 0.19999999999999 values. [image: Screen Shot 2019-12-18 at 2.58.36 AM.png] I also tried your 'example' but, also, I have similar results. Am I making some errors? Thanks, Maurizio.

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Re: [External] DIPY IVIM does not work correctly
by Fadnavis, Shreyas Sanjeev 20 Dec '19

20 Dec '19

Hi Maurizio, I'd be happy to take a look. It would be convenient if you could share the script and data that you are using! Thanks, Shreyas On 18 Dec 2019 01:58, Maurizio Bergamino <maurizio.bergamino(a)gmail.com> wrote: This message was sent from a non-IU address. Please exercise caution when clicking links or opening attachments from external sources. Hello, I am using DIPY for the first time because I would like to analyze IVIM data. I created my python script and I ran the fit for my data. However, the results are not, in my opinion, correct. I analyzed only one slice, because the script needs time, and I wanted to be sure that it worked correctly. However, for the f index, I have 3/4 of the brain with 0.19999999999999 values. [Screen Shot 2019-12-18 at 2.58.36 AM.png] I also tried your 'example' but, also, I have similar results. Am I making some errors? Thanks, Maurizio.

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