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import urllib.parse |
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from ...utils import compress |
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from ...data import ScalarImage, LabelMap |
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from ...download import download_and_extract_archive |
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from .mni import SubjectMNI |
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TISSUES_2008 = { |
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1: 'Cerebro-spinal fluid', |
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2: 'Gray Matter', |
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3: 'White Matter', |
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4: 'Fat', |
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5: 'Muscles', |
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6: 'Skin and Muscles', |
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7: 'Skull', |
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9: 'Fat 2', |
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10: 'Dura', |
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11: 'Marrow', |
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12: 'Vessels', |
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} |
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class Colin27(SubjectMNI): |
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r"""Colin27 MNI template. |
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More information can be found in the website of the |
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`1998 <http://nist.mni.mcgill.ca/?p=935>`_ and |
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`2008 <http://www.bic.mni.mcgill.ca/ServicesAtlases/Colin27Highres>`_ |
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versions. |
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.. image:: http://www.bic.mni.mcgill.ca/uploads/ServicesAtlases/mni_colin27_2008.jpg |
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:alt: MNI Colin 27 2008 version |
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Arguments: |
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version: Template year. It can be ``1998`` or ``2008``. |
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.. warning:: The resolution of the ``2008`` version is quite high. The |
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subject instance will contain four images of size |
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:math:`362 \times 434 \times 362`, therefore applying a transform to |
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it might take longer than expected. |
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Example: |
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>>> import torchio as tio |
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>>> colin_1998 = tio.datasets.Colin27(version=1998) |
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>>> colin_1998 |
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Colin27(Keys: ('t1', 'head', 'brain'); images: 3) |
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>>> colin_1998.load() |
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>>> colin_1998.t1 |
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ScalarImage(shape: (1, 181, 217, 181); spacing: (1.00, 1.00, 1.00); orientation: RAS+; memory: 27.1 MiB; type: intensity) |
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>>> |
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>>> colin_2008 = tio.datasets.Colin27(version=2008) |
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>>> colin_2008 |
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Colin27(Keys: ('t1', 't2', 'pd', 'cls'); images: 4) |
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>>> colin_2008.load() |
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>>> colin_2008.t1 |
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ScalarImage(shape: (1, 362, 434, 362); spacing: (0.50, 0.50, 0.50); orientation: RAS+; memory: 217.0 MiB; type: intensity) |
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""" # noqa: E501 |
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def __init__(self, version=1998): |
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if version not in (1998, 2008): |
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raise ValueError(f'Version must be 1998 or 2008, not "{version}"') |
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self.version = version |
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self.name = f'mni_colin27_{version}_nifti' |
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self.url_dir = urllib.parse.urljoin(self.url_base, 'colin27/') |
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self.filename = f'{self.name}.zip' |
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self.url = urllib.parse.urljoin(self.url_dir, self.filename) |
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if not self.download_root.is_dir(): |
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download_and_extract_archive( |
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self.url, |
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download_root=self.download_root, |
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filename=self.filename, |
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) |
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# Fix label map (https://github.com/fepegar/torchio/issues/220) |
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if version == 2008: |
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path = self.download_root / 'colin27_cls_tal_hires.nii' |
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cls_image = LabelMap(path) |
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cls_image.set_data(cls_image.data.round().byte()) |
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cls_image.save(path) |
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(self.download_root / self.filename).unlink() |
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for path in self.download_root.glob('*.nii'): |
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compress(path) |
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path.unlink() |
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try: |
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subject_dict = self.get_subject_dict(extension='.nii.gz') |
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except FileNotFoundError: # for backward compatibility |
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subject_dict = self.get_subject_dict(extension='.nii') |
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super().__init__(subject_dict) |
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def get_subject_dict(self, extension): |
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if self.version == 1998: |
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t1, head, mask = [ |
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self.download_root / f'colin27_t1_tal_lin{suffix}{extension}' |
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for suffix in ('', '_headmask', '_mask') |
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] |
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subject_dict = { |
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't1': ScalarImage(t1), |
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'head': LabelMap(head), |
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'brain': LabelMap(mask), |
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} |
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elif self.version == 2008: |
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t1, t2, pd, label = [ |
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self.download_root / f'colin27_{name}_tal_hires{extension}' |
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for name in ('t1', 't2', 'pd', 'cls') |
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] |
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subject_dict = { |
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't1': ScalarImage(t1), |
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't2': ScalarImage(t2), |
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'pd': ScalarImage(pd), |
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'cls': LabelMap(label, labels=TISSUES_2008), |
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} |
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return subject_dict |
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fepegar /
torchio
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