0016_lidc/README_0016_lidc.md

# LIDC-IDRI – Lung Image Database Consortium and Image Database Resource Initiative

## License
**CC BY 3.0**  
[Creative Commons Attribution 3.0 Unported License](https://creativecommons.org/licenses/by/3.0/)

## Citation
Paper BibTeX:

```bibtex
@article{armato2011lung,
  title={The lung image database consortium (LIDC) and image database resource initiative (IDRI): a completed reference database of lung nodules on CT scans},
  author={Armato III, Samuel G and McLennan, Geoffrey and Bidaut, Luc and McNitt-Gray, Michael F and Meyer, Charles R and Reeves, Anthony P and Zhao, Binsheng and Aberle, Denise R and Henschke, Claudia I and Hoffman, Eric A and others},
  journal={Medical physics},
  volume={38},
  number={2},
  pages={915--931},
  year={2011},
  publisher={Wiley Online Library}
}
```

Dataset:

```bibtex
Armato III, S. G., McLennan, G., Bidaut, L., McNitt-Gray, M. F., Meyer, C. R., Reeves, A. P., Zhao, B., Aberle, D. R., Henschke, C. I., Hoffman, E. A., Kazerooni, E. A., MacMahon, H., Van Beek, E. J. R., Yankelevitz, D., Biancardi, A. M., Bland, P. H., Brown, M. S., Engelmann, R. M., Laderach, G. E., Max, D., Pais, R. C. , Qing, D. P. Y. , Roberts, R. Y., Smith, A. R., Starkey, A., Batra, P., Caligiuri, P., Farooqi, A., Gladish, G. W., Jude, C. M., Munden, R. F., Petkovska, I., Quint, L. E., Schwartz, L. H., Sundaram, B., Dodd, L. E., Fenimore, C., Gur, D., Petrick, N., Freymann, J., Kirby, J., Hughes, B., Casteele, A. V., Gupte, S., Sallam, M., Heath, M. D., Kuhn, M. H., Dharaiya, E., Burns, R., Fryd, D. S., Salganicoff, M., Anand, V., Shreter, U., Vastagh, S., Croft, B. Y., Clarke, L. P. (2015). Data From LIDC-IDRI [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/K9/TCIA.2015.LO9QL9SX
```


## Dataset description
The LIDC-IDRI dataset contains diagnostic and lung cancer screening thoracic CT scans with annotated lesions, created through a multi-institutional public–private partnership. Each of the 1,018 cases underwent a two-phase review by four thoracic radiologists to comprehensively identify lung nodules without requiring consensus, supporting CAD system development and evaluation.

**Number of CT volumes**: 997

**CT type**: Standard-dose and low-dose helical thoracic CTs

**CT body coverage**: Chest

**Does the dataset include any ground truth annotations?**: Yes

**Original GT annotation targets**: Lung nodules

**Number of annotated CT volumes**: -

**Annotator**: Human

**Acquisition centers**: Seven academic centers and eight medical imaging companies

**Pathology/Disease**: Lung nodules (benign or malignant)

**Original dataset download link**: https://www.cancerimagingarchive.net/collection/lidc-idri/

**Original dataset format**: DICOM