Note
Go to the end to download the full example code. or to run this example in your browser via Binder
Plotting tools in nilearn¶
Nilearn comes with a set of plotting functions for easy visualization of Nifti-like images such as statistical maps mapped onto anatomical images or onto glass brain representation, anatomical images, functional/EPI images, region specific mask images.
See Plotting brain images for more details.
We will first retrieve data from nilearn provided (general-purpose) datasets.
from nilearn import datasets
# haxby dataset to have EPI images and masks
haxby_dataset = datasets.fetch_haxby()
# print basic information on the dataset
print(
f"First subject anatomical nifti image (3D) is at: {haxby_dataset.anat[0]}"
)
print(
f"First subject functional nifti image (4D) is at: {haxby_dataset.func[0]}"
)
haxby_anat_filename = haxby_dataset.anat[0]
haxby_mask_filename = haxby_dataset.mask_vt[0]
haxby_func_filename = haxby_dataset.func[0]
# one motor activation map
stat_img = datasets.load_sample_motor_activation_image()
[get_dataset_dir] Dataset found in /home/runner/nilearn_data/haxby2001
First subject anatomical nifti image (3D) is at: /home/runner/nilearn_data/haxby2001/subj2/anat.nii.gz
First subject functional nifti image (4D) is at: /home/runner/nilearn_data/haxby2001/subj2/bold.nii.gz
Nilearn plotting functions¶
Plotting statistical maps: plot_stat_map¶
from nilearn import plotting
Visualizing t-map image on EPI template with manual positioning of coordinates using cut_coords given as a list
plotting.plot_stat_map(
stat_img, threshold=3, title="plot_stat_map", cut_coords=[36, -27, 66]
)
![plot demo plotting](../../_images/sphx_glr_plot_demo_plotting_001.png)
<nilearn.plotting.displays._slicers.OrthoSlicer object at 0x7f7a892f3370>
It’s also possible to visualize volumes in a LR-flipped “radiological” view Just set radiological=True
plotting.plot_stat_map(
stat_img,
threshold=3,
title="plot_stat_map",
cut_coords=[36, -27, 66],
radiological=True,
)
![plot demo plotting](../../_images/sphx_glr_plot_demo_plotting_002.png)
<nilearn.plotting.displays._slicers.OrthoSlicer object at 0x7f7a895413d0>
Making interactive visualizations: view_img¶
An alternative to plot_stat_map
is to use
view_img
that gives more interactive
visualizations in a web browser. See Interactive visualization of statistical map slices
for more details.
view = plotting.view_img(stat_img, threshold=3)
# In a Jupyter notebook, if ``view`` is the output of a cell, it will
# be displayed below the cell
view
/home/runner/work/nilearn/nilearn/.tox/doc/lib/python3.9/site-packages/numpy/core/fromnumeric.py:758: UserWarning: Warning: 'partition' will ignore the 'mask' of the MaskedArray.
a.partition(kth, axis=axis, kind=kind, order=order)
# uncomment this to open the plot in a web browser:
# view.open_in_browser()
Plotting statistical maps in a glass brain: plot_glass_brain¶
Now, the t-map image is mapped on glass brain representation where glass brain is always a fixed background template
plotting.plot_glass_brain(stat_img, title="plot_glass_brain", threshold=3)
![plot demo plotting](../../_images/sphx_glr_plot_demo_plotting_003.png)
<nilearn.plotting.displays._projectors.OrthoProjector object at 0x7f7a8938fbe0>
Plotting anatomical images: plot_anat¶
Visualizing anatomical image of haxby dataset
plotting.plot_anat(haxby_anat_filename, title="plot_anat")
![plot demo plotting](../../_images/sphx_glr_plot_demo_plotting_004.png)
<nilearn.plotting.displays._slicers.OrthoSlicer object at 0x7f7a853cdbb0>
Plotting ROIs (here the mask): plot_roi¶
Visualizing ventral temporal region image from haxby dataset overlaid on subject specific anatomical image with coordinates positioned automatically on region of interest (roi)
plotting.plot_roi(
haxby_mask_filename, bg_img=haxby_anat_filename, title="plot_roi"
)
![plot demo plotting](../../_images/sphx_glr_plot_demo_plotting_005.png)
<nilearn.plotting.displays._slicers.OrthoSlicer object at 0x7f7a8938bee0>
Plotting EPI image: plot_epi¶
# Import image processing tool
from nilearn import image
# Compute the voxel_wise mean of functional images across time.
# Basically reducing the functional image from 4D to 3D
mean_haxby_img = image.mean_img(haxby_func_filename, copy_header=True)
# Visualizing mean image (3D)
plotting.plot_epi(mean_haxby_img, title="plot_epi")
![plot demo plotting](../../_images/sphx_glr_plot_demo_plotting_006.png)
<nilearn.plotting.displays._slicers.OrthoSlicer object at 0x7f7a8510ba00>
A call to plotting.show is needed to display the plots when running in script mode (ie outside IPython)
Thresholding plots¶
Using threshold
value alongside with vmin
and vmax
parameters
enable us to mask certain values in the image.
Plotting without threshold¶
plotting.plot_stat_map(
stat_img,
display_mode="ortho",
cut_coords=[36, -27, 60],
title="No plotting threshold",
)
![plot demo plotting](../../_images/sphx_glr_plot_demo_plotting_007.png)
<nilearn.plotting.displays._slicers.OrthoSlicer object at 0x7f7a895cb1c0>
Plotting threshold set to 1¶
When plotting threshold is set to 1, the values between -1 and 1 are masked in the plot.
plotting.plot_stat_map(
stat_img,
threshold=1,
display_mode="ortho",
cut_coords=[36, -27, 60],
title="plotting threshold=1",
)
![plot demo plotting](../../_images/sphx_glr_plot_demo_plotting_008.png)
<nilearn.plotting.displays._slicers.OrthoSlicer object at 0x7f7a89486880>
Plotting threshold set to 1 with vmin=0
¶
Setting vmin=0
, it is possible to plot only positive image values.
plotting.plot_stat_map(
stat_img,
threshold=1,
cmap="inferno",
display_mode="ortho",
cut_coords=[36, -27, 60],
title="plotting threshold=1, vmin=0",
vmin=0,
)
![plot demo plotting](../../_images/sphx_glr_plot_demo_plotting_009.png)
<nilearn.plotting.displays._slicers.OrthoSlicer object at 0x7f7a7c511820>
Plotting threshold set to 1 with vmax=0
¶
Setting vmax=0
, it is possible to plot only negative image values.
plotting.plot_stat_map(
stat_img,
threshold=1,
cmap="inferno",
display_mode="ortho",
cut_coords=[36, -27, 60],
title="plotting threshold=1, vmax=0",
vmax=0,
)
![plot demo plotting](../../_images/sphx_glr_plot_demo_plotting_010.png)
<nilearn.plotting.displays._slicers.OrthoSlicer object at 0x7f7a85a91dc0>
Visualizing without a colorbar on the right side¶
The argument colorbar
should be set to False
to show plots without
a colorbar on the right side.
plotting.plot_stat_map(
stat_img,
display_mode="ortho",
cut_coords=[36, -27, 60],
colorbar=False,
title="no colorbar",
)
![plot demo plotting](../../_images/sphx_glr_plot_demo_plotting_011.png)
<nilearn.plotting.displays._slicers.OrthoSlicer object at 0x7f7a89388640>
Total running time of the script: (0 minutes 20.449 seconds)
Estimated memory usage: 1005 MB