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title | Data Access |
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| Data AccessData Type | Download all or Query/Filter | License |
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Images and Segmentations (DICOM, 201.2 GB) |
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url | https://wiki.cancerimagingarchive.net/download/attachments/6885289/QIN-HEADNECK%20NBIA-manifest.tcia_20200914.tcia?api=v2 |
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label | Search |
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url | https://nbia.cancerimagingarchive.net/nbia-search/?MinNumberOfStudiesCriteria=1&CollectionCriteria=QIN-HEADNECK |
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(Download requires the NBIA Data Retriever) | | Clinical Data (.xlsx 68 kB) (See also Detailed Description) |
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url | https://wiki.cancerimagingarchive.net/download/attachments/6885289/Batch_01%20and%20Batch_02%20Clinical%20Data_aug242020.xlsx?api=v2 |
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Localtab |
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title | Detailed Description |
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| Detailed Description
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Modalities | PET, CT, SR, SEG, RWV | Number of Participants | 279 | Number of Studies | 1032 | Number of Series | 3837 | Number of Images | 701,002 | Image Size (GB) | 201.2 | - Structured Report DICOM objects (Modality SR), are available for a subset of these subjects in the DICOM downloads and can be distinguished from image files by the series description "Clinical Data." Note, there is no image preview thumbnail for a Structured Report.
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title | Citations & Data Usage Policy |
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| Citations & Data Usage Policy Tcia limited license policy |
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Info |
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| Beichel, R. R., Ulrich, E. J., Bauer, C., Wahle, A., Brown, B., Chang, T., Plichta, K A., Smith, B J., Sunderland, J J., Braun, T., Fedorov, A., Clunie, D., Onken, M., Magnotta VA, V. A., Menda, Y., Riesmeier, J., Pieper, S., Kikinis, R., Graham, M.M., Casavant T. L., Sonka M,. & Buatti, J M. (2015). Data From QIN-HEADNECK (Version 4) [Data set]. The Cancer Imaging Archive. DOI: https://doi.org/10.7937/K9/TCIA.2015.K0F5CGLI |
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title | Publication Citation |
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| Fedorov, A., Clunie, D., Ulrich, E., Bauer, C., Wahle, A., Brown, B., Onken, M., Riesmeier, J., Pieper, S., Kikinis, R., Buatti, J., & Beichel RR, R. R. (2016). DICOM for quantitative imaging biomarker development: a standards based approach to sharing clinical data and structured PET/CT analysis results in head and neck cancer research. In PeerJ (Vol. 4:e2057 DOI: , p. e2057). PeerJ. https://doi.org/10.7717/peerj.2057 |
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| Clark, K., Vendt, B., Smith, K., Freymann, J., Kirby, J., Koppel, P., Moore, S., Phillips, S., Maffitt, D., Pringle, M., Tarbox, L., & Prior, F. (2013). The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository, . In Journal of Digital Imaging , Volume (Vol. 26, Number Issue 6, December, 2013, pp 1045-1057. DOI: pp. 1045–1057). Springer Science and Business Media LLC. https://doi.org/10.1007/s10278-013-9622-7 PMCID: PMC3824915 |
Other Publications Using This DataTCIA maintains a list of publications that which leverage our data, including citations of this CollectionTCIA data. If you have a publication manuscript you'd like to add please contact the TCIA's Helpdesk. Some publications that have used this dataset as a resource include Taghanaki et al. Segmentation-free direct tumor volume and metabolic activity estimation from PET scans. Comput Med Imaging Graph 2018 link to article . - Ahmadvand, P., Duggan, N., Bénard, F., & Hamarneh, G. (2016). Tumor Lesion Segmentation from 3D PET Using a Machine Learning Driven Active Surface. International Workshop on Machine Learning in Medical Imaging. doi: 10.1007/978-3-319-47157-0_33
- Fedorov, A., Beichel, R., Kalpathy-Cramer, J., Clunie, D., Onken, M., Riesmeier, J., . . . Kikinis, R. (2020). Quantitative Imaging Informatics for Cancer Research. JCO Clin Cancer Inform, 4, 444-453. doi:https://doi.org/10.1200/CCI.19.00165
- Fedorov, A., Clunie, D., Ulrich, E., Bauer, C., Wahle, A., Brown, B., . . . Beichel, R. R. (2016). DICOM for quantitative imaging biomarker development: a standards based approach to sharing clinical data and structured PET/CT analysis results in head and neck cancer research. PeerJ, 4, e2057. doi: 10.7717/peerj.2057
- Ghattas, A. E. (2017). Medical Imaging Segmentation Assessment via Bayesian Approaches to Fusion, Accuracy and Variability Estimation with Application to Head and Neck Cancer. (PhD). The University of Iowa, Retrieved from http://ir.uiowa.edu/etd/5759
- Liang, X., Bassenne, M., Hristov, D. H., Islam, M. T., Zhao, W., Jia, M., . . . Xing, L. (2022). Human-level comparable control volume mapping with a deep unsupervised-learning model for image-guided radiation therapy. Comput Biol Med, 141, 105139. doi: 10.1016/j.compbiomed.2021.105139
- 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: 10.1016/j.cmpb.2023.107341
- Sinha, A. (2018). Deformable registration using shape statistics with applications in sinus surgery. (Ph. D.). Johns Hopkins University, Retrieved from http://jhir.library.jhu.edu/handle/1774.2/59202
- Sinha, A., Billings, S. D., Reiter, A., Liu, X., Ishii, M., Hager, G. D., & Taylor, R. H. (2019). The deformable most-likely-point paradigm. Medical image analysis, 55, 148-164. doi: 10.1016/j.media.2019.04.013
- Sinha et al. Towards automatic initialization of registration algorithms using simulated endoscopy images. link to article
Ghattas, Andrew Emile Medical Imaging Segmentation Assessment via Bayesian Approaches to Fusion, Accuracy and Variability Estimation with Application to Head and Neck Cancer 2017 Thesis link Stoll et al- Sinha, A., Ishii, M., Hager, G. D., & Taylor, R. H. (2019). Endoscopic navigation in the clinic: registration in the absence of preoperative imaging. Int J Comput Assist Radiol Surg, 14(9), 1495-1506. doi: 10.1007/s11548-019-02005-0
- Smith, B. J., Buatti, J. M., Bauer, C., Ulrich, E. J., Ahmadvand, P., Budzevich, M. M., . . . Beichel, R. R. (2020). Multisite Technical and Clinical Performance Evaluation of Quantitative Imaging Biomarkers from 3D FDG PET Segmentations of Head and Neck Cancer Images. Tomography, 6(2), 65-76. doi: 10.18383/j.tom.2020.00004
- Stoll, M., Stoiber, E. M., Grimm, S., Debus, J., Bendl, R., & Giske, K. (2016). Comparison of Safety Margin Generation Concepts in Image Guided Radiotherapy to Account for Daily Head and Neck Pose Variations
PLoS One 2016 link to article Ahmadvand et al. Tumor Lesion Segmentation from 3D PET Using a Machine Learning Driven Active Surface 2016 MLMI Conference Proceedings link to article - . PLoS One, 11(12), e0168916. doi: 10.1371/journal.pone.0168916
- Taghanaki, S. A., Duggan, N., Ma, H., Hou, X., Celler, A., Benard, F., & Hamarneh, G. (2018). Segmentation-free direct tumor volume and metabolic activity estimation from PET scans. Comput Med Imaging Graph, 63, 52-66. doi: 10.1016/j.compmedimag.2017.12.004
- Thomas, R., Schalck, E., Fourure, D., Bonnefoy, A., & Cervera-Marzal, I. (2021). 2Be3-Net: Combining 2D and 3D Convolutional Neural Networks for 3D PET Scans Predictions. Paper presented at the International Conference on Medical Imaging and Computer-Aided Diagnosis (MICAD 2021). doi: 10.1007/978-981-16-3880-0_27
- Trebeschi, S., Bodalal, Z., van Dijk, N., Boellaard, T. N., Apfaltrer, P., Tareco Bucho, T. M., . . . Beets-Tan, R. G. H. (2021). Development of a Prognostic AI-Monitor for Metastatic Urothelial Cancer Patients Receiving Immunotherapy. Front Oncol, 11, 637804. doi: 10.3389/fonc.2021.637804
- Vrtovec, T., Močnik, D., Strojan, P., Pernuš, F., & Ibragimov, B. (2020). Auto‐segmentation of organs at risk for head and neck radiotherapy planning: from atlas‐based to deep learning methods. Medical Physics, 47, e929-e950. doi: 10.1002/mp.14320
- Zschaeck, S., Li, Y., Lin, Q., Beck, M., Amthauer, H., Bauersachs, L., . . . Hofheinz, F. (2020). Prognostic value of baseline [18F]-fluorodeoxyglucose positron emission tomography parameters MTV, TLG and asphericity in an international multicenter cohort of nasopharyngeal carcinoma patients. PLoS One, 15(7), e0236841. doi: 10.1371/journal.pone.0236841
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Localtab |
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| Version 4 (Current) : Updated 2020/09/15 Data Type | Download all or Query/Filter |
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Images and Segmentations (DICOM 201.2 GB) |
Tcia button generator |
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url | https://wiki.cancerimagingarchive.net/download/attachments/6885289/QIN-HEADNECK%20NBIA-manifest.tcia_20200914.tcia?api=v2 |
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label | Search |
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url | https://nbia.cancerimagingarchive.net/nbia-search/?MinNumberOfStudiesCriteria=1&CollectionCriteria=QIN-HEADNECK |
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(Download requires the NBIA Data Retriever) | Clinical Data (.xlsx 68 kB) |
Tcia button generator |
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url | https://wiki.cancerimagingarchive.net/download/attachments/6885289/Batch_01%20and%20Batch_02%20Clinical%20Data_aug242020.xlsx?api=v2 |
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| Added 123 new subjects (Patient IDs = QIN-HeadNeck-02-####). Added missing PT or CT pre-treatment and follow up scans to 28 of the previously existing QIN-HeadNeck-01-#### subjects. Added supporting clinical data in XLSX format for all patients. Version 3: Updated 2019/07/24 Data Type | Download all or Query/Filter |
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Images (DICOM, 103.5 GB) |
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url | https://wiki.cancerimagingarchive.net/download/attachments/6885289/TCIA_QIN-HEADNECK_2019-07-24.tcia?version=3&modificationDate=1563997513437&api=v2 |
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| DICOM Metadata Digest (CSV) |
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url | https://wiki.cancerimagingarchive.net/download/attachments/6885289/QIN-HEADNECK_TCIAmanifest_metadata_Jul2019.csv?version=2&modificationDate=1563997454543&api=v2 |
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| Lifted restriction from SR object data download. Version 2: Updated 2017/12/06Downloads require the NBIA Data Retriever . Data Type | Download all or Query/Filter |
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Images (DICOM, 104 GB) |
Tcia button generator |
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url | https://wiki.cancerimagingarchive.net/download/attachments/6885289/QIN-HEADNECK-12-06-2017-doiJNLP-Hb7bP6pf.tcia?version=1&modificationDate=1534786972624&api=v2 |
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| DICOM Metadata Digest (CSV) |
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url | https://wiki.cancerimagingarchive.net/download/attachments/6885289/QIN-HEADNECK_MetaData.csv?version=1&modificationDate=1495728510607&api=v2 |
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| Added associated DICOM SEG, SR, and RWV objects Version 1: Updated 2015/08/20 Data Type | Download all or Query/Filter |
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Images (DICOM, 102.76 GB) |
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url | https://wiki.cancerimagingarchive.net/download/attachments/6885289/TCIA_QIN-HEADNECK_06-22-2015.tcia?version=1&modificationDate=1534787423317&api=v2 |
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| DICOM Metadata Digest (CSV) |
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url | https://wiki.cancerimagingarchive.net/download/attachments/6885289/QIN-HEADNECK_MetaData.csv?version=1&modificationDate=1495728510607&api=v2 |
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