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.
nilearn.datasets.fetch_icbm152_2009#
- nilearn.datasets.fetch_icbm152_2009(data_dir=None, url=None, resume=True, verbose=1)[source]#
Download and load the ICBM152 template (dated 2009).
The default template of fMRIPrep is the asymmetrical ICBM152 2009, release c (MNI152NLin2009cSAsym). The NiLearn template is asymmetrical ICBM152 2009, release a. If you wish to use the exact same release as fMRIPrep, please refer to TemplateFlow (https://www.templateflow.org/).
For more information, see 1, 2, and 3.
- Parameters
- data_dir
pathlib.Pathorstr, optional Path where data should be downloaded. By default, files are downloaded in home directory.
- url
str, optional URL of file to download. Override download URL. Used for test only (or if you setup a mirror of the data). Default=None.
- resume
bool, optional Whether to resume download of a partly-downloaded file. Default=True.
- verbose
int, optional Verbosity level (0 means no message). Default=1.
- data_dir
- Returns
- datasklearn.datasets.base.Bunch
Dictionary-like object, interest keys are:
“t1”: str, Path to T1-weighted anatomical image
“t2”: str, Path to T2-weighted anatomical image
“t2_relax”: str, Path to anatomical image obtained with the T2 relaxometry
“pd”: str, Path to the proton density weighted anatomical image
“gm”: str, Path to grey matter segmented image
“wm”: str, Path to white matter segmented image
“csf”: str, Path to cerebrospinal fluid segmented image
“eye_mask”: str, Path to eye mask useful to mask out part of MRI images
“face_mask”: str, Path to face mask useful to mask out part of MRI images
“mask”: str, Path to whole brain mask useful to mask out skull areas
See also
nilearn.datasets.load_mni152_templateto load MNI152 T1 template.
nilearn.datasets.load_mni152_gm_templateto load MNI152 grey matter template.
nilearn.datasets.load_mni152_wm_templateto load MNI152 white matter template.
nilearn.datasets.load_mni152_brain_maskto load MNI152 whole brain mask.
nilearn.datasets.load_mni152_gm_maskto load MNI152 grey matter mask.
nilearn.datasets.load_mni152_wm_maskto load MNI152 white matter mask.
nilearn.datasets.fetch_icbm152_brain_gm_maskto fetch only ICBM grey matter mask.
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
TemplateFlow repository for ICBM152 2009
Symmetric: https://github.com/templateflow/tpl-MNI152NLin2009cSym
Asymmetric: https://github.com/templateflow/tpl-MNI152NLin2009cSAsym
References
- 1
Vladimir Fonov, Alan C. Evans, Kelly Botteron, C. Robert Almli, Robert C. McKinstry, and D. Louis Collins. Unbiased average age-appropriate atlases for pediatric studies. NeuroImage, 54(1):313–327, 2011. URL: https://www.sciencedirect.com/science/article/pii/S1053811910010062, doi:https://doi.org/10.1016/j.neuroimage.2010.07.033.
- 2
VS Fonov, AC Evans, RC McKinstry, CR Almli, and DL Collins. Unbiased nonlinear average age-appropriate brain templates from birth to adulthood. NeuroImage, 47(Supplement 1):S102, 2009. doi:10.1016/S1053-8119(09)70884-5.
- 3
D. Louis Collins, Alex P. Zijdenbos, Wim F. C. Baaré, and Alan C. Evans. Animal+insect: improved cortical structure segmentation. In Attila Kuba, Martin Šáamal, and Andrew Todd-Pokropek, editors, Information Processing in Medical Imaging, 210–223. Berlin, Heidelberg, 1999. Springer Berlin Heidelberg.
