Localtab |
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active | true |
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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. Data Type | Download all or Query/Filter |
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Gross Tumor Volume Segmentation - (DICOM RTSTRUCT and SEG, 912 MB) | | Corresponding Original CT Images from RIDER Lung CT - (DICOM, 7 GB) | |
Click the Versions tab for more info about data releases. Collections Used in this Third Party Analysis Below is a list of the Collections used in these analyses: |
Localtab |
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title | Detailed Description |
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| Detailed DescriptionImage Statistics |
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Modalities (DICOM) | RTSTRUCT, SEG | Number of Patients | 31 | Number of Studies | 31 | Number of Series | 118 | Number of Images | 118 | Images Size (GB) | 912 MB |
(RIDER-2283289298) only has segmentations associated with the retest. (RIDER-5195703382) only has segmentations associated with the test. (RIDER-8509201188) only has segmentations associated with the test. (RIDER-9762593735) not included in the data set due to missing delineations.
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Localtab |
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title | Citations & Data Usage Policy |
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| Citations & Data Usage Policy Users of this data must abide by the Creative Commons Attribution-NonCommercial 3.0 Unported License under which it has been published. Attribution should include references to the following citations: Info |
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| Leonard Wee, L., Hugo Aerts, H., Petros Kalendralis and Andre DekkerKalendralis, P., & Dekker, A. (20182020). RIDER Lung CT Segmentation Labels from: Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/tcia.2020.jit9grk8 |
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 . (2013). 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)), 1045–1057. https://doi.org/10.1007/s10278-013-9622-7 |
Info |
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title | Publication Citation |
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| Aerts, H. J. W. L., Velazquez, E. R., Leijenaar, R. T. H., Parmar, C., Grossmann, P., CavalhoCarvalho, S., Bussink, J., Monshouwer, R., Haibe-Kains, B., Rietveld, D., Hoebers, F., … , Rietbergen, M. M., Leemans, C. R., Dekker, A., Quackenbush, J., Gillies, R. J., & Lambin, P. (2014, June 3). Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach. Nature Communications. Nature Publishing Group. http, 5(1). https://doi.org/10.1038/ncomms5006 |
Questions may be directed to help@cancerimagingarchive.net. Other Publications Using This DataTCIA maintains a list of publications that leverage TCIA data. If you have a manuscript you'd like to add please contact the TCIA Helpdesk. |
Localtab |
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| Version 1 (Current): Updated 2020/02/13Data Type | Download all or Query/Filter |
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Gross Tumor Volume Segmentation - (DICOM RTSTRUCT and SEG, 912 MB) | | Corresponding Original CT Images from RIDER Lung CT - (DICOM, 7 GB) | |
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