Basic Atlas plotting

Plot the regions of a reference atlas (Harvard-Oxford and Juelich atlases).

Retrieving the atlas data

from nilearn import datasets

dataset_ho = datasets.fetch_atlas_harvard_oxford("cort-maxprob-thr25-2mm")
dataset_ju = datasets.fetch_atlas_juelich("maxprob-thr0-1mm")

atlas_ho_filename = dataset_ho.filename
atlas_ju_filename = dataset_ju.filename

print(f"Atlas ROIs are located at: {atlas_ho_filename}")
print(f"Atlas ROIs are located at: {atlas_ju_filename}")

Dataset created in /home/remi/nilearn_data/fsl

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Extracting data from /home/remi/nilearn_data/fsl/c4d84bbdf5c3325f23e304cdea1e9706/HarvardOxford.tgz..... done.
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Extracting data from /home/remi/nilearn_data/fsl/ab1b53038e13028e55f691a69003c208/Juelich.tgz..... done.
Atlas ROIs are located at: /home/remi/nilearn_data/fsl/data/atlases/HarvardOxford/HarvardOxford-cort-maxprob-thr25-2mm.nii.gz
Atlas ROIs are located at: /home/remi/nilearn_data/fsl/data/atlases/Juelich/Juelich-maxprob-thr0-1mm.nii.gz

Visualizing the Harvard-Oxford atlas

from nilearn import plotting

plotting.plot_roi(atlas_ho_filename, title="Harvard Oxford atlas")

<nilearn.plotting.displays._slicers.OrthoSlicer object at 0x7fd1f296e910>

Visualizing the Juelich atlas

plotting.plot_roi(atlas_ju_filename, title="Juelich atlas")

<nilearn.plotting.displays._slicers.OrthoSlicer object at 0x7fd1e32e8f90>

Visualizing the Harvard-Oxford atlas with contours

plotting.plot_roi(
    atlas_ho_filename,
    view_type="contours",
    title="Harvard Oxford atlas in contours",
)
plotting.show()

/home/remi/github/nilearn/env/lib/python3.11/site-packages/nilearn/plotting/img_plotting.py:608: UserWarning: Data array used to create a new image contains 64-bit ints. This is likely due to creating the array with numpy and passing `int` as the `dtype`. Many tools such as FSL and SPM cannot deal with int64 in Nifti images, so for compatibility the data has been converted to int32.
  img = new_img_like(roi_img, data, affine=roi_img.affine)

Visualizing the Juelich atlas with contours

plotting.plot_roi(
    atlas_ju_filename, view_type="contours", title="Juelich atlas in contours"
)
plotting.show()

Estimated memory usage: 435 MB