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Training Data

The purpose of the data within this repository is to collate the datasets that are utilised to build the public Radiotherapy AI models.

References

TCIA

Clark K, Vendt B, Smith K, Freymann J, Kirby J, Koppel P, Moore S, Phillips S, Maffitt D, Pringle M, Tarbox L, Prior F. The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository, Journal of Digital Imaging, Volume 26, Number 6, December, 2013, pp 1045-1057. DOI: 10.1007/s10278-013-9622-7

4D-Lung

https://wiki.cancerimagingarchive.net/display/Public/4D-Lung#212674141d3f10cc8f084cec86132755a57a1d9c

Hugo, Geoffrey D., Weiss, Elisabeth, Sleeman, William C., Balik, Salim, Keall, Paul J., Lu, Jun, & Williamson, Jeffrey F. (2016). Data from 4D Lung Imaging of NSCLC Patients. The Cancer Imaging Archive. http://doi.org/10.7937/K9/TCIA.2016.ELN8YGLE

Hugo, G. D., Weiss, E., Sleeman, W. C., Balik, S., Keall, P. J., Lu, J. and Williamson, J. F. (2017), A longitudinal four-dimensional computed tomography and cone beam computed tomography dataset for image-guided radiation therapy research in lung cancer. Med. Phys., 44: 762-771. doi:10.1002/mp.12059

S. Balik et al., "Evaluation of 4-Dimensional Computed Tomography to 4-Dimensional Cone-Beam Computed Tomography Deformable Image Registration for Lung Cancer Adaptive Radiation Therapy." Int. J. Radiat. Oncol. Biol. Phys. 86, 372-9 (2013) PMCID: PMC3647023.

N.O. Roman, W. Shepherd, N. Mukhopadhyay, G.D. Hugo, and E. Weiss, "Interfractional Positional Variability of Fiducial Markers and Primary Tumors in Locally Advanced Non-Small-Cell Lung Cancer during Audiovisual Biofeedback Radiotherapy." Int. J. Radiat. Oncol. Biol. Phys. 83, 1566-72 (2012). DOI:10.1016/j.ijrobp.2011.10.051

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