Mailman 3 Reg. IVIM processing using DIPY - DIPY

June 27, 2020

      Dear Experts,

I tried to process ivim data by following https://www.frontiersin.org/articles/10.3389/fninf.2014.00008/full and https://dipy.org/documentation/1.1.1./examples_built/reconst_ivim/.
However, I am unable to get output.

I will be highly obliged if you can examine the log below and advice.

Best Regards,
Amitkumar J. Choudhari,
Assistant Professor, Dept. of Radiology,
Tata Memorial Hospital, Mumbai.
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fimg = "dwi.nii.gz"
import nibabel as nib
img = nib.load(fimg)
data = img.get_data()
<stdin>:1: DeprecationWarning: get_data() is deprecated in favor of get_fdata(), which has a more predictable return type. To obtain get_data() behavior going forward, use numpy.asanyarray(img.dataobj).
* deprecated from version: 3.0
* Will raise <class 'nibabel.deprecator.ExpiredDeprecationError'> as of version: 5.0
...
...
...
data.shape
(176, 176, 23, 43)
affine = img.get_affine()
<stdin>:1: DeprecationWarning: get_affine method is deprecated.
Please use the ``img.affine`` property instead.
* deprecated from version: 2.1
* Will raise <class 'nibabel.deprecator.ExpiredDeprecationError'> as of version: 4.0
...
...
...
header = img.get_header()
<stdin>:1: DeprecationWarning: get_header method is deprecated.
Please use the ``img.header`` property instead.
* deprecated from version: 2.1
* Will raise <class 'nibabel.deprecator.ExpiredDeprecationError'> as of version: 4.0
...
...
...
header = img.get_header()
voxel_size = header.get_zooms()[:3]
voxel_size
(1.3068181, 1.3068181, 6.0)
...
S0 = data[:, :, :, 0]
img2 = nib.Nifti1Image(S0, affine)
nib.save (img2, "sub_data.nii.gz")
from dipy.segment.mask import median_otsu
mask, S0_mask = median_otsu(data [:, :, :, 0])
fbval = "dwi.bval"
fbvec = "dwi.bvec"
from dipy.io<http://dipy.io/> import read_bvals_bvecs
bvals, bvecs = read_bvals_bvecs(fbval, fbvec)
from dipy.core.gradients import gradient_table
gtab = gradient_table(bvals, bvecs)
gtab
<dipy.core.gradients.GradientTable object at 0x7f7265d78820>
import matplotlib.pyplot as plt
import numpy as np
from dipy.reconst.ivim import IvimModel
from dipy.data import get_fnameshttps://dipy.org/documentation/1.1.1./examples_built/reconst_ivim/<http://dipy.org/documentation/1.1.1./examples_built/reconst_ivim/>
from dipy.io.image import load_nifti_data
fraw, fbval, fbvec = get_fnames('ivim')
Download Progress: [########################################] 100.00%  of 0.00 MB>>>
data = img.get_data()
<stdin>:1: DeprecationWarning: get_data() is deprecated in favor of get_fdata(), which has a more predictable return type. To obtain get_data() behavior going forward, use numpy.asanyarray(img.dataobj).
* deprecated from version: 3.0
* Will raise <class 'nibabel.deprecator.ExpiredDeprecationError'> as of version: 5.0
...
...
...
bvals, bvecs = read_bvals_bvecs(fbval, fbvec)
gtab = gradient_table(bvals, bvecs, b0_threshold=0)
print('data.shape (%d, %d, %d, %d)' % data.shape)
data.shape (176, 176, 23, 43)
z = 12
b = 0
plt.imshow(data[:, :, z, b].T, origin='lower', cmap='gray',
...            interpolation='nearest')
<matplotlib.image.AxesImage object at 0x7f723009d5e0>
plt.axhline(y=100)
<matplotlib.lines.Line2D object at 0x7f7233b643a0>
plt.axvline(x=170)
<matplotlib.lines.Line2D object at 0x7f723009dd00>
plt.savefig("ivim_data_slice.png")
plt.close()
ivimmodel = IvimModel(gtab, fit_method='trr')
/home/amitjc/.local/lib/python3.8/site-packages/dipy/reconst/ivim.py:147: UserWarning: Bounds for this fit have been set from experiments and literature survey. To change the bounds, please input your bounds in model definition...
  warnings.warn(bounds_warning, UserWarning)
x1, x2 = 50, 125
y1, y2 = 40, 140
data_slice = data[x1:x2, y1:y2, z, :]
plt.imshow(data[x1:x2, y1:y2, z, b].T, origin='lower',
...            cmap="gray", interpolation='nearest')
<matplotlib.image.AxesImage object at 0x7f72232b7c70>
plt.savefig("CSF_slice.png")
plt.close()
ivimmodel = IvimModel(gtab, fit_method='trr')
ivimfit = ivimmodel.fit(data_slice)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/amitjc/.local/lib/python3.8/site-packages/dipy/reconst/multi_voxel.py", line 33, in new_fit
    fit_array[ijk] = single_voxel_fit(self, data[ijk])
  File "/home/amitjc/.local/lib/python3.8/site-packages/dipy/reconst/ivim.py", line 317, in fit
    S0_prime, D = self.estimate_linear_fit(
  File "/home/amitjc/.local/lib/python3.8/site-packages/dipy/reconst/ivim.py", line 377, in estimate_linear_fit
    -np.log(data[self.gtab.bvals >=
IndexError: boolean index did not match indexed array along dimension 0; dimension is 43 but corresponding boolean dimension is 21

Reg. IVIM processing using DIPY

Amit Choudhari

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