""" ================================================= 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[..., 5] bvals_small = bvals[5] bvecs_small = bvecs[5, ...] gtab = gradient_table(bvals, bvecs) """ Start motion correction of our reduced DWI dataset(between-volumes motion correction). """ data_corrected, reg_afines = motion_correction(data, gtab, affine) """ Save our DWI dataset corrected to a new Nifti file. """ save_nifti('motion_correction.nii.gz', data_corrected.get_fdata(), 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 """