Source code for torchio.datasets.mni.colin

import urllib.parse

from ...utils import compress
from ...data import ScalarImage, LabelMap
from ...download import download_and_extract_archive
from .mni import SubjectMNI


TISSUES_2008 = {
    1: 'Cerebro-spinal fluid',
    2: 'Gray Matter',
    3: 'White Matter',
    4: 'Fat',
    5: 'Muscles',
    6: 'Skin and Muscles',
    7: 'Skull',
    9: 'Fat 2',
    10: 'Dura',
    11: 'Marrow',
    12: 'Vessels',
}


[docs]class Colin27(SubjectMNI): r"""Colin27 MNI template. More information can be found in the website of the `1998 <http://nist.mni.mcgill.ca/?p=935>`_ and `2008 <http://www.bic.mni.mcgill.ca/ServicesAtlases/Colin27Highres>`_ versions. .. image:: http://www.bic.mni.mcgill.ca/uploads/ServicesAtlases/mni_colin27_2008.jpg :alt: MNI Colin 27 2008 version Arguments: version: Template year. It can be ``1998`` or ``2008``. .. warning:: The resolution of the ``2008`` version is quite high. The subject instance will contain four images of size :math:`362 \times 434 \times 362`, therefore applying a transform to it might take longer than expected. Example: >>> import torchio as tio >>> colin_1998 = tio.datasets.Colin27(version=1998) >>> colin_1998 Colin27(Keys: ('t1', 'head', 'brain'); images: 3) >>> colin_1998.load() >>> colin_1998.t1 ScalarImage(shape: (1, 181, 217, 181); spacing: (1.00, 1.00, 1.00); orientation: RAS+; memory: 27.1 MiB; type: intensity) >>> >>> colin_2008 = tio.datasets.Colin27(version=2008) >>> colin_2008 Colin27(Keys: ('t1', 't2', 'pd', 'cls'); images: 4) >>> colin_2008.load() >>> colin_2008.t1 ScalarImage(shape: (1, 362, 434, 362); spacing: (0.50, 0.50, 0.50); orientation: RAS+; memory: 217.0 MiB; type: intensity) """ # noqa: E501 def __init__(self, version=1998): if version not in (1998, 2008): raise ValueError(f'Version must be 1998 or 2008, not "{version}"') self.version = version self.name = f'mni_colin27_{version}_nifti' self.url_dir = urllib.parse.urljoin(self.url_base, 'colin27/') self.filename = f'{self.name}.zip' self.url = urllib.parse.urljoin(self.url_dir, self.filename) if not self.download_root.is_dir(): download_and_extract_archive( self.url, download_root=self.download_root, filename=self.filename, ) # Fix label map (https://github.com/fepegar/torchio/issues/220) if version == 2008: path = self.download_root / 'colin27_cls_tal_hires.nii' cls_image = LabelMap(path) cls_image.set_data(cls_image.data.round().byte()) cls_image.save(path) (self.download_root / self.filename).unlink() for path in self.download_root.glob('*.nii'): compress(path) path.unlink() try: subject_dict = self.get_subject_dict(extension='.nii.gz') except FileNotFoundError: # for backward compatibility subject_dict = self.get_subject_dict(extension='.nii') super().__init__(subject_dict) def get_subject_dict(self, extension): if self.version == 1998: t1, head, mask = [ self.download_root / f'colin27_t1_tal_lin{suffix}{extension}' for suffix in ('', '_headmask', '_mask') ] subject_dict = { 't1': ScalarImage(t1), 'head': LabelMap(head), 'brain': LabelMap(mask), } elif self.version == 2008: t1, t2, pd, label = [ self.download_root / f'colin27_{name}_tal_hires{extension}' for name in ('t1', 't2', 'pd', 'cls') ] subject_dict = { 't1': ScalarImage(t1), 't2': ScalarImage(t2), 'pd': ScalarImage(pd), 'cls': LabelMap(label, labels=TISSUES_2008), } return subject_dict