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"""LyNoS: Mediastinal lymph nodes segmentation using 3D convolutional neural network ensembles and anatomical priors guiding.""" |
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import datasets |
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_DESCRIPTION = """\ |
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LyNoS: Mediastinal lymph nodes segmentation using 3D convolutional neural network ensembles and anatomical priors guiding. |
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""" |
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_HOMEPAGE = "https://github.com/raidionics/LyNoS" |
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_LICENSE = "MIT" |
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_CITATION = """\ |
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@article{bouget2023mediastinal, |
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title={Mediastinal lymph nodes segmentation using 3D convolutional neural network ensembles and anatomical priors guiding}, |
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author={Bouget, David and Pedersen, Andr{\'e} and Vanel, Johanna and Leira, Haakon O and Lang{\o}, Thomas}, |
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journal={Computer Methods in Biomechanics and Biomedical Engineering: Imaging \& Visualization}, |
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volume={11}, |
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number={1}, |
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pages={44--58}, |
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year={2023}, |
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publisher={Taylor \& Francis} |
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} |
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""" |
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_URLS = [ |
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{ |
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"ct": f"data/Pat{i}/Pat{i}_data.nii.gz", |
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"azygos": f"data/Pat{i}/Pat{i}_labels_Azygos.nii.gz", |
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"brachiocephalicveins": f"data/Pat{i}/Pat{i}_labels_BrachiocephalicVeins.nii.gz", |
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"esophagus": f"data/Pat{i}/Pat{i}_labels_Esophagus.nii.gz", |
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"lymphnodes": f"data/Pat{i}/Pat{i}_labels_LymphNodes.nii.gz", |
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"subclaviancarotidarteries": f"data/Pat{i}/Pat{i}_labels_SubCarArt.nii.gz", |
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} |
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for i in range(1, 15) |
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] |
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class LyNoS(datasets.GeneratorBasedBuilder): |
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"""A segmentation benchmark dataset for enlarged lymph nodes in patients with primary lung cancer.""" |
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VERSION = datasets.Version("1.0.0") |
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def _info(self): |
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features = datasets.Features( |
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{ |
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"ct": datasets.Value("string"), |
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"lymphnodes": datasets.Value("string"), |
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} |
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) |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION, |
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features=features, |
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homepage=_HOMEPAGE, |
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license=_LICENSE, |
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citation=_CITATION, |
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) |
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def _split_generators(self, dl_manager): |
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data_dirs = dl_manager.download(_URLS) |
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return [ |
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datasets.SplitGenerator( |
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name=datasets.Split.TEST, |
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gen_kwargs={ |
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"data_dirs": data_dirs, |
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}, |
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), |
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] |
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def _generate_examples(self, data_dirs): |
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for key, patient in enumerate(data_dirs): |
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yield key, patient |
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