.. only:: html .. note:: :class: sphx-glr-download-link-note Click :ref:`here ` to download the full example code or to run this example in your browser via Binder .. rst-class:: sphx-glr-example-title .. _sphx_glr_auto_examples_01_plotting_plot_3d_map_to_surface_projection.py: Making a surface plot of a 3D statistical map ============================================= project a 3D statistical map onto a cortical mesh using :func:`nilearn.surface.vol_to_surf`. Display a surface plot of the projected map using :func:`nilearn.plotting.plot_surf_stat_map` and adding contours of regions of interest using :func:`nilearn.plotting.plot_surf_contours`. Get a statistical map --------------------- .. code-block:: default from nilearn import datasets motor_images = datasets.fetch_neurovault_motor_task() stat_img = motor_images.images[0] Get a cortical mesh ------------------- .. code-block:: default fsaverage = datasets.fetch_surf_fsaverage() Sample the 3D data around each node of the mesh ----------------------------------------------- .. code-block:: default from nilearn import surface texture = surface.vol_to_surf(stat_img, fsaverage.pial_right) Plot the result --------------- .. code-block:: default from nilearn import plotting plotting.plot_surf_stat_map(fsaverage.infl_right, texture, hemi='right', title='Surface right hemisphere', colorbar=True, threshold=1., bg_map=fsaverage.sulc_right) .. image:: /auto_examples/01_plotting/images/sphx_glr_plot_3d_map_to_surface_projection_001.png :alt: Surface right hemisphere :class: sphx-glr-single-img .. rst-class:: sphx-glr-script-out Out: .. code-block:: none

Plot 3D image for comparison ---------------------------- .. code-block:: default plotting.plot_glass_brain(stat_img, display_mode='r', plot_abs=False, title='Glass brain', threshold=2.) plotting.plot_stat_map(stat_img, display_mode='x', threshold=1., cut_coords=range(0, 51, 10), title='Slices') .. rst-class:: sphx-glr-horizontal * .. image:: /auto_examples/01_plotting/images/sphx_glr_plot_3d_map_to_surface_projection_002.png :alt: plot 3d map to surface projection :class: sphx-glr-multi-img * .. image:: /auto_examples/01_plotting/images/sphx_glr_plot_3d_map_to_surface_projection_003.png :alt: plot 3d map to surface projection :class: sphx-glr-multi-img .. rst-class:: sphx-glr-script-out Out: .. code-block:: none Use an atlas and choose regions to outline ------------------------------------------ .. code-block:: default import numpy as np destrieux_atlas = datasets.fetch_atlas_surf_destrieux() parcellation = destrieux_atlas['map_right'] # these are the regions we want to outline regions_dict = {b'G_postcentral': 'Postcentral gyrus', b'G_precentral': 'Precentral gyrus'} # get indices in atlas for these labels regions_indices = [np.where(np.array(destrieux_atlas['labels']) == region)[0][0] for region in regions_dict] labels = list(regions_dict.values()) Display outlines of the regions of interest on top of a statistical map ----------------------------------------------------------------------- .. code-block:: default figure = plotting.plot_surf_stat_map(fsaverage.infl_right, texture, hemi='right', title='Surface right hemisphere', colorbar=True, threshold=1., bg_map=fsaverage.sulc_right) plotting.plot_surf_contours(fsaverage.infl_right, parcellation, labels=labels, levels=regions_indices, figure=figure, legend=True, colors=['g', 'k']) plotting.show() .. image:: /auto_examples/01_plotting/images/sphx_glr_plot_3d_map_to_surface_projection_004.png :alt: Surface right hemisphere :class: sphx-glr-single-img Plot with higher-resolution mesh -------------------------------- `fetch_surf_fsaverage` takes a "mesh" argument which specifies whether to fetch the low-resolution fsaverage5 mesh, or the high-resolution fsaverage mesh. using mesh="fsaverage" will result in more memory usage and computation time, but finer visualizations. .. code-block:: default big_fsaverage = datasets.fetch_surf_fsaverage('fsaverage') big_texture = surface.vol_to_surf(stat_img, big_fsaverage.pial_right) plotting.plot_surf_stat_map(big_fsaverage.infl_right, big_texture, hemi='right', colorbar=True, title='Surface right hemisphere: fine mesh', threshold=1., bg_map=big_fsaverage.sulc_right) .. image:: /auto_examples/01_plotting/images/sphx_glr_plot_3d_map_to_surface_projection_005.png :alt: Surface right hemisphere: fine mesh :class: sphx-glr-single-img .. rst-class:: sphx-glr-script-out Out: .. code-block:: none

Plot multiple views of the 3D volume on a surface ------------------------------------------------- *plot_img_on_surf* takes a statistical map and projects it onto a surface. It supports multiple choices of orientations, and can plot either one or both hemispheres. If no *surf_mesh* is given, *plot_img_on_surf* projects the images onto `FreeSurfer `_\'s fsaverage5. .. code-block:: default plotting.plot_img_on_surf(stat_img, views=['lateral', 'medial'], hemispheres=['left', 'right'], colorbar=True) plotting.show() .. image:: /auto_examples/01_plotting/images/sphx_glr_plot_3d_map_to_surface_projection_006.png :alt: plot 3d map to surface projection :class: sphx-glr-single-img 3D visualization in a web browser --------------------------------- An alternative to :func:`nilearn.plotting.plot_surf_stat_map` is to use :func:`nilearn.plotting.view_surf` or :func:`nilearn.plotting.view_img_on_surf` that give more interactive visualizations in a web browser. See :ref:`interactive-surface-plotting` for more details. .. code-block:: default view = plotting.view_surf(fsaverage.infl_right, texture, threshold='90%', bg_map=fsaverage.sulc_right) # In a Jupyter notebook, if ``view`` is the output of a cell, it will # be displayed below the cell view .. raw:: html

.. code-block:: default # uncomment this to open the plot in a web browser: # view.open_in_browser() We don't need to do the projection ourselves, we can use view_img_on_surf: .. code-block:: default view = plotting.view_img_on_surf(stat_img, threshold='90%') # view.open_in_browser() view .. raw:: html

Impact of plot parameters on visualization ------------------------------------------ You can specify arguments to be passed on to the function :func:`nilearn.surface.vol_to_surf` using `vol_to_surf_kwargs`. This allows fine-grained control of how the input 3D image is resampled and interpolated - for example if you are viewing a volumetric atlas, you would want to avoid averaging the labels between neighboring regions. Using nearest-neighbor interpolation with zero radius will achieve this. .. code-block:: default destrieux = datasets.fetch_atlas_destrieux_2009() view = plotting.view_img_on_surf( destrieux.maps, surf_mesh="fsaverage", vol_to_surf_kwargs={"n_samples": 1, "radius": 0.0, "interpolation": "nearest"}, symmetric_cmap=False, ) # view.open_in_browser() view .. rst-class:: sphx-glr-script-out Out: .. code-block:: none /home/nicolas/anaconda3/envs/nilearn/lib/python3.8/site-packages/numpy/lib/npyio.py:2405: VisibleDeprecationWarning: Reading unicode strings without specifying the encoding argument is deprecated. Set the encoding, use None for the system default. output = genfromtxt(fname, **kwargs) .. raw:: html

.. rst-class:: sphx-glr-timing **Total running time of the script:** ( 0 minutes 23.267 seconds) .. _sphx_glr_download_auto_examples_01_plotting_plot_3d_map_to_surface_projection.py: .. only :: html .. container:: sphx-glr-footer :class: sphx-glr-footer-example .. container:: binder-badge .. image:: images/binder_badge_logo.svg :target: https://mybinder.org/v2/gh/nilearn/nilearn.github.io/main?filepath=examples/auto_examples/01_plotting/plot_3d_map_to_surface_projection.ipynb :alt: Launch binder :width: 150 px .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: plot_3d_map_to_surface_projection.py ` .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: plot_3d_map_to_surface_projection.ipynb ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_