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title | Data Access |
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| Data AccessClick the Download button to save a ".tcia" manifest file to your computer, which you must open with the NBIA Data Retriever. Click the Search button to open our Data Portal, where you can browse the data collection and/or download a subset of its contents. Data Type | Download all or Query/Filter |
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Images (DICOM, 104GB103 GiB) | | DICOM Metadata Digest (CSV) | | Clinical data | (See Detailed Description tab) |
Click the Versions tab for more info about data releases. |
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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 Patients | 156 | Number of Studies | 651 | Number of Series | 4292993 | Number of Images | 353,408 | Image Size (GB) | 104103 |
MetadataStructured Report DICOM objects (Modality SR), are available 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 ReportAccess to this collection's clinical data is restricted due to the type of information included and/or the informed consent procedure under which the data were collected. If you believe this data will be useful for a current or planned research project, you may request access to this clinical data by completing the attached Data Use Agreement and forwarding it via e-mail to the TCIA help desk (help@cancerimagingarchive.net). The Data Use Agreement will be promptly reviewed by a TCIA review committee and you will be informed of their decision. In most cases access will be granted and members of your research team will be granted access to the clinical data. Note: you must have TCIA login credentials in order to access any restricted collection. |
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title | Citations & Data Usage Policy |
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| Citations & Data Usage Policy This collection is freely available to browse, download, and use for commercial, scientific and educational purposes as outlined in the Creative Commons Attribution 3.0 Unported License. See TCIA's Data Usage Policies and Restrictions for additional details. Questions may be directed to help@cancerimagingarchive.net. Please be sure to include the following citations in your work if you use this data set: 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, Riesmeier J, Pieper S, Kikinis R, Graham M M, Casavant T L, Sonka M, Buatti J M. (2015). Data From QIN-HEADNECK. The Cancer Imaging Archive. http://doi.org/DOI: 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. (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 https://doi.org/e2057 DOI: 10.7717/peerj.2057 |
Info |
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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. 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. (paper). DOI: 10.1007/s10278-013-9622-7 |
Other Publications Using This DataTCIA maintains a list of publications that leverage our data, including citations of this Collection. If you have a publication you'd like to add please contact the TCIA 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
- 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. 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
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Localtab |
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| Version 2 3 (Current) : Updated 2019/07/24Data Type | Download all or Query/Filter |
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Images (DICOM, 103 GB) | | DICOM Metadata Digest (CSV) | |
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, 104GB104 GB) | | DICOM Metadata Digest (CSV) | |
Added associated DICOM SEG, SR, and RWV objects Version 1: Updated 2015/08/20Data Type | Download all or Query/Filter |
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Images (DICOM, 102.76GB76 GB) | | DICOM Metadata Digest (CSV) | |
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