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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 | License |
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Gross Tumor Volume Segmentation - | 31 subjects (DICOM RTSTRUCT and SEG, 912 MB) |
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url | https://wiki.cancerimagingarchive.net/download/attachments/46334165/RIDER%20Lung%20CT%20RTSTRUCTS%20DICOM%20SEGS%20Leonard%20Wee%20Feb%2010%202020.tcia?api=v2 |
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Collections Used in this Third Party AnalysisBelow is a list of the Collections used in these analyses: Source Data Type | Download all or Query/Filter | License |
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Image Removed 31 subjects | Click the Versions tab for more info about data releases. |
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url | https://wiki.cancerimagingarchive.net/download/attachments/46334165/RIDER%20Lung%20CT%20Original%20Scans%20for%20Leonard%20Wee%20Feb%2010%202020%20.tcia?api=v2 |
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title | Detailed Description |
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| Detailed DescriptionRadiology Image Statistics |
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Modalities (DICOM) | RTSTRUCT, SEG | , CT | Number of Patients | 31 | Number of Studies | 31 | Number of Series | 118 | Number of Images | 118 | Image 7.9 | Note(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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title | Citations & Data Usage Policy |
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| Citations & Data Usage Policy This analysis set may not be used for commercial purposes. It is available to browse, download, as outlined in the Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0) https://creativecommons.org/licenses/by-nc/3.0/. See TCIA's Data Usage Policies and Restrictions for additional details. Questions may be directed to help@cancerimagingarchive.net. Tcia limited license policy |
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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 | In addition to the dataset citation above, please be sure to cite the following if you utilize these data in your research:
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title | Publication TCIA Citation |
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| AertsClark, H. J. W. L., Velazquez, E. R., Leijenaar, R. T. H., Parmar, C., Grossmann, P., Cavalho, S., … Lambin, P. (2014, June 3). Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach. Nature Communications. Nature Publishing Group. httpK., 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. Journal of Digital Imaging, 26(6), 1045–1057. https://doi.org/10.1038/ncomms50061007/s10278-013-9622-7 |
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title | RIDER Lung CT Data Publication Citation |
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| Zhao, Binsheng, SchwartzAerts, Lawrence H, & Kris, Mark G. (2015). Data From RIDER_Lung CT. The Cancer Imaging Archive. DOI: 10.7937/K9/TCIA.2015.U1X8A5NR | Info |
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title | RIDER Lung CT Publication Citation |
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| Zhao, B., James, L. P., Moskowitz, C. S., Guo, P., Ginsberg, M. S., Lefkowitz, R. A.,Qin, Y. Riely, G.J., Kris, M.G., Schwartz, L. H. (2009, July). Evaluating Variability in Tumor Measurements from Same-day Repeat CT Scans of Patients with Non–Small Cell Lung Cancer 1 . Radiology. Radiological Society of North America (RSNA). DOI: 10.1148/radiol.2522081593 (paper). J. W. L., Velazquez, E. R., Leijenaar, R. T. H., Parmar, C., Grossmann, P., Carvalho, 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). Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach. Nature Communications, 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 2020/13/022 (Current): Updated 2021/10/28Data 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) | |
The authors of this dataset agreed to change the license to permit commercial use. The actual dataset remains unchanged. Version 1: Updated 2020/02/13Data Type | Download all or Query/Filter |
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Gross Tumor Volume Segmentation - | 31 subjects (DICOM RTSTRUCT and SEG, 912 MB) | | Corresponding Original CT Images from RIDER Lung CT | 31 subjects
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