
"""

=================================================
Between-volumes Motion Correction on DWI datasets
=================================================

Overview
--------
During a dMRI acquisition, the subject motion inevitable. This motion implies
a misalignment between N volumes on a dMRI dataset. A common way to solve this
issue is to perform a registration on each acquired volume to a
reference b = 0. [JenkinsonSmith01]_

This preprocessing is an highly recommended step that should be executed before
any dMRI dataset analysis.


Let's import some essential functions.
"""

from dipy.align import motion_correction
from dipy.core.gradients import gradient_table
from dipy.data import get_fnames
from dipy.io.image import load_nifti, save_nifti
from dipy.io.gradients import read_bvals_bvecs

"""
We choose one of the data from the datasets in dipy_. However, you can
replace the following line with the path of your image.
"""

dwi_fname, dwi_bval_fname, dwi_bvec_fname = get_fnames('sherbrooke_3shell')

"""
We load the image and the affine of the image. The affine is the transformation
matrix which maps image coordinates to world (mm) coordinates. We also load the
b-values and b-vectors.
"""

data, affine = load_nifti(dwi_fname)
bvals, bvecs = read_bvals_bvecs(dwi_bval_fname, dwi_bvec_fname)

"""
This data has 193 volumes. For this demo purpose, we decide to reduce the
number of volumes to 5. However, we do not recommended to perform a motion
correction with less than 10 volumes.
"""

data_small = data[..., :3]
bvals_small = bvals[:3]
bvecs_small = bvecs[:3]
gtab = gradient_table(bvals_small, bvecs_small)

"""
Start motion correction of our reduced DWI dataset(between-volumes motion
correction).
"""

data_corrected, reg_affines = motion_correction(data_small, gtab, affine)

"""
Save our DWI dataset corrected to a new Nifti file.
"""

save_nifti('motion_correction.nii.gz', data_corrected.get_fdata(),
           data_corrected.affine)

"""
References
----------

.. [JenkinsonSmith01] Jenkinson, M., Smith, S., 2001. A global optimisation
   method for robust affine registration of brain images. Med Image Anal 5
   (2), 143–56.

.. include:: ../links_names.inc
"""
