EXACT'09 – Extraction of Airways from CT

License

The original data sets and associated segmentation data downloaded here, or any data derived from these data sets, must not be given nor redistributed under any circumstances to persons not belonging to the registered team.

Citation

Paper BibTeX:

@article{lo2012extraction,
  title={Extraction of airways from CT (EXACT'09)},
  author={Lo, Pechin and Van Ginneken, Bram and Reinhardt, Joseph M and Yavarna, Tarunashree and De Jong, Pim A and Irving, Benjamin and Fetita, Catalin and Ortner, Margarete and Pinho, R{\^o}mulo and Sijbers, Jan and others},
  journal={IEEE Transactions on Medical Imaging},
  volume={31},
  number={11},
  pages={2093--2107},
  year={2012},
  publisher={IEEE}
}

Dataset description

The goal of the EXACT study is to compare algorithms to extract the airway tree from chest CT scans using a common dataset and performance evaluation method.

Challenge homepage: https://image.diku.dk/exact/index.php

Number of CT volumes: 40

Contrast: Various scanning conditions (contrast and non-contrast)

CT body coverage: Chest

Does the dataset include any ground truth annotations?: Yes

Original GT annotation targets: Airway trees

Number of annotated CT volumes: -

Annotator: Algorithmic segmentation with visual scoring by trained observers

Acquisition centers: Eight institutions

Pathology/Disease: From healthy subjects to severe airway and lung abnormalities

Original dataset download link: -

Original dataset format: DICOM

Note:

This dataset is subject to a customized license. The original CT image download link is no longer valid.

To respect the original dataset’s intended use and license terms, we do not openly redistribute the data here. Researchers interested in accessing the images and/or supplementary segmentation annotations for the intended use of the dataset may contact us ([email protected]) to explore access options, potentially within a joint research collaboration.

If you would rather not go through this process, please feel free to skip this dataset and continue with the other data provided in our CADS-dataset.