.. _sphx_glr_auto_examples_01_template_plot_register.py:


Registration to common space
============================

Here we show how to create a template from multiple anatomical scans and
register all of them to it.
Initially, registration is of extracted brains. Once these are reasonably
aligned, whole heads are registered, weighted by masks that, if parameters
are chosen well, include some scalp. The amount of scalp is hopefully enough
to help in differentiating the brain-scalp boundary without including so much
head tissue that it starts to contaminate the registration with the highly
variable head tissue.


Retrieve the data
-----------------



.. code-block:: python

    from sammba import data_fetchers

    lemur = data_fetchers.fetch_lemur_mircen_2019_t2(subjects=[0, 1, 2])







retest contains paths to images and data description



.. code-block:: python

    print(lemur.anat)





.. rst-class:: sphx-glr-script-out

 Out::

    ['/home/salma/nilearn_data/mircen2019_t2/sub-01/sub-01_anat_sub-01_T2w.nii.gz', '/home/salma/nilearn_data/mircen2019_t2/sub-02/sub-02_anat_sub-02_T2w.nii.gz', '/home/salma/nilearn_data/mircen2019_t2/sub-03/sub-03_anat_sub-03_T2w.nii.gz']


Define the writing directory
----------------------------



.. code-block:: python

    import os

    write_dir = os.path.join(os.getcwd(), 'lemur_common')
    if not os.path.exists(write_dir):
        os.makedirs(write_dir)







Create the template
-------------------



.. code-block:: python

    from sammba.registration import anats_to_common

    affine_register = anats_to_common(lemur.anat, write_dir, 400,
                                      use_rats_tool=False, caching=True)







We set caching to True, so that the computations are not restarted.
The paths to the registered images can be accessed easilly



.. code-block:: python

    registered_anats = affine_register.registered
    print(registered_anats)





.. rst-class:: sphx-glr-script-out

 Out::

    ['/home/salma/CODE/sammba-mri/examples/01_template/lemur_common/sub-01_anat_sub-01_T2w_0_Unifized_for_brain_extraction_resample_shr_affine_catenated.nii.gz', '/home/salma/CODE/sammba-mri/examples/01_template/lemur_common/sub-02_anat_sub-02_T2w_1_Unifized_for_brain_extraction_resample_shr_affine_catenated.nii.gz', '/home/salma/CODE/sammba-mri/examples/01_template/lemur_common/sub-03_anat_sub-03_T2w_2_Unifized_for_brain_extraction_resample_shr_affine_catenated.nii.gz']


Assess the template
-------------------



.. code-block:: python

    from nilearn import image
    template_img = image.mean_img(registered_anats)







Visalize results
----------------
We plot the edges of one individual anat on top of the average image



.. code-block:: python

    from nilearn import plotting

    average_img = image.mean_img(registered_anats)
    display = plotting.plot_anat(average_img, dim=-1.6, title='affine register')
    display.add_edges(registered_anats[0])
    plotting.show()




.. image:: /auto_examples/01_template/images/sphx_glr_plot_register_001.png
    :align: center




Visualize pipeline steps
-------------------------



.. code-block:: python

    from sammba.graphs import create_pipeline_graph

    graph_file = os.path.join(write_dir, 'affine_registration_graph')
    create_pipeline_graph('anats_to_common_affine', graph_file)






**Total running time of the script:** ( 51 minutes  0.667 seconds)



.. container:: sphx-glr-footer


  .. container:: sphx-glr-download

     :download:`Download Python source code: plot_register.py <plot_register.py>`



  .. container:: sphx-glr-download

     :download:`Download Jupyter notebook: plot_register.ipynb <plot_register.ipynb>`

.. rst-class:: sphx-glr-signature

    `Generated by Sphinx-Gallery <https://sphinx-gallery.readthedocs.io>`_