Page History

Data Access

Some data in this collection contains images that could potentially be used to reconstruct a human face. To safeguard the privacy of participants, users must sign and submit a TCIA No Commercial Limited Access License to help@cancerimagingarchive.net before accessing the data.

Click the Versions tab for more info about data releases.

Detailed Description

Citations & Data Usage Policy

Questions may be directed to help@cancerimagingarchive.net. 

Other Publications Using This Data

TCIA maintains a list of publications which leverage our data. If you have a manuscript you'd like to add please contact the TCIA Helpdesk.

1. Bielak, L., Wiedenmann, N., Berlin, A., Nicolay, N. H., Gunashekar, D. D., Hagele, L., . . . Bock, M. (2020). Convolutional neural networks for head and neck tumor segmentation on 7-channel multiparametric MRI: a leave-one-out analysis. Radiat Oncol, 15(1), 181. doi:https://doi.org/10.1186/s13014-020-01618-z
2. Choi, Y., Nam, Y., Jang, J., Shin, N. Y., Ahn, K. J., Kim, B. S., . . . Kim, M. S. (2020). Prediction of Human Papillomavirus Status and Overall Survival in Patients with Untreated Oropharyngeal Squamous Cell Carcinoma: Development and Validation of CT-Based Radiomics. AJNR Am J Neuroradiol, 41(10), 1897-1904. doi: https://doi.org/10.3174/ajnr.A6756 
3. Gifford, R. C. (2022). Deep Learning Architecture to Improve Edge Accuracy of Auto-Contouring for Head and Neck Radiotherapy. (Master of Science MS). Ohio State UNiversity, Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=osu1658317931555616 
4. Giraud, P., Giraud, P., Nicolas, E., Boisselier, P., Alfonsi, M., Rives, M., . . . Chajon, E. (2021). Interpretable Machine Learning Model for Locoregional Relapse Prediction in Oropharyngeal Cancers. Cancers, 13(1), 57. doi:https://doi.org/10.3390/cancers13010057
5. Kalendralis, P. (2022). Artificial intelligence applications in radiotherapy: The role of the FAIR data principles. (Ph.D. Dissertation). Maastricht University ,The Netherlands, Available from https://doi.org/10.26481/dis.20221010pk 
6. Kalendralis, P., Shi, Z., Traverso, A., Choudhury, A., Sloep, M., Zhovannik, I., . . . Wee, L. (2020). FAIR-compliant clinical, radiomics and DICOM metadata of RIDER, interobserver, Lung1 and head-Neck1 TCIA collections. Med Phys. doi:https://doi.org/10.1002/mp.14322
7. La Greca Saint-Esteven, A., Bogowicz, M., Konukoglu, E., Riesterer, O., Balermpas, P., Guckenberger, M., . . . van Timmeren, J. E. (2022). A 2.5D convolutional neural network for HPV prediction in advanced oropharyngeal cancer. Comput Biol Med, 142, 105215. doi:https://doi.org/10.1016/j.compbiomed.2022.105215 
8. Li, J., Qiu, Z., Zhang, C., Chen, S., Wang, M., Meng, Q., . . . Zhang, X. (2022). ITHscore: comprehensive quantification of intra-tumor heterogeneity in NSCLC by multi-scale radiomic features. Eur Radiol. doi:https://doi.org/10.1007/s00330-022-09055-0 
9. Lombardo, E., Kurz, C., Marschner, S., Avanzo, M., Gagliardi, V., Fanetti, G., . . . Landry, G. (2021). Distant metastasis time to event analysis with CNNs in independent head and neck cancer cohorts. Sci Rep, 11(1), 6418. doi:https://doi.org/10.1038/s41598-021-85671-y 
10. Lv, W., Zhou, Z., Peng, J., Peng, L., Lin, G., Wu, H., . . . Lu, L. (2023). Functional-structural Sub-region Graph Convolutional Network (FSGCN): Application to the Prognosis of Head and Neck Cancer with PET/CT imaging. Computer Methods and Programs in Biomedicine. doi:https://doi.org/10.1016/j.cmpb.2023.107341
11. Moitra, D., & Mandal, R. K. (2022). Classification of malignant tumors by a non-sequential recurrent ensemble of deep neural network model. Multimed Tools Appl, 1-19. doi:https://doi.org/10.1007/s11042-022-12229-z 
12. Zhinan, L., Wei, Z., Yudi, Y., Yabing, D., Yuanzhe, X., & Xiulan, L. (2022). Prediction of Human Papillomavirus (HPV) Status in Oropharyngeal Squamous Cell Carcinoma Based on Radiomics and Machine Learning Algorithms: A Multi-Cohort Study. Systematic Reviews in Pharmacy. 

Version 3 (Current): Updated 2020/07/29

Added the chemotherapy schedule to the clinical data; one extra column added which is “chemotherapy_given”.

Added data dictionary for clinical data.

Version 2: Updated 2019/09/20

Added DICOM Segmentations

Version 1: Updated 2019/07/25