Note

This page is a reference documentation. It only explains the function signature, and not how to use it. Please refer to the user guide for the big picture.

8.2.19. nilearn.datasets.fetch_icbm152_2009

nilearn.datasets.fetch_icbm152_2009(data_dir=None, url=None, resume=True, verbose=1)

Download and load the ICBM152 template (dated 2009).

For more information, see [1], [2], and [3].

Parameters
data_dirstring, optional

Path of the data directory. Used to force data storage in a non- standard location. Default: None (meaning: default)

urlstring, optional

Download URL of the dataset. Overwrite the default URL.

resumebool, optional

If True, try resuming partially downloaded data. Default=True.

verboseint, optional

Verbosity level (0 means no message). Default=1.

Returns
datasklearn.datasets.base.Bunch

Dictionary-like object, interest keys are: “t1”, “t2”, “t2_relax”, “pd”: anatomical images obtained with the given modality (resp. T1, T2, T2 relaxometry and proton density weighted). Values are file paths. “gm”, “wm”, “csf”: segmented images, giving resp. gray matter, white matter and cerebrospinal fluid. Values are file paths. “eye_mask”, “face_mask”, “mask”: use these images to mask out parts of mri images. Values are file paths.

Notes

For more information about this dataset’s structure: http://www.bic.mni.mcgill.ca/ServicesAtlases/ICBM152NLin2009

The original download URL is http://www.bic.mni.mcgill.ca/~vfonov/icbm/2009/mni_icbm152_nlin_sym_09a_nifti.zip

References

1

VS Fonov, AC Evans, K Botteron, CR Almli, RC McKinstry, DL Collins and BDCG, “Unbiased average age-appropriate atlases for pediatric studies”, NeuroImage,Volume 54, Issue 1, January 2011

2

VS Fonov, AC Evans, RC McKinstry, CR Almli and DL Collins, “Unbiased nonlinear average age-appropriate brain templates from birth to adulthood”, NeuroImage, Volume 47, Supplement 1, July 2009, Page S102 Organization for Human Brain Mapping 2009 Annual Meeting.

3

DL Collins, AP Zijdenbos, WFC Baare and AC Evans, “ANIMAL+INSECT: Improved Cortical Structure Segmentation”, IPMI Lecture Notes in Computer Science, 1999, Volume 1613/1999, 210-223