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| title | Data Access |
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| Data Access| Data Type | Download all or Query/Filter | License |
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| Gross Tumor Volume Segmentation - (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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(Requires NBIA Data Retriever.) | |
Click the Versions tab for more info about data releases. 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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| Corresponding Original CT Images from RIDER Lung CT - (DICOM, 7 GB) |
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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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(Requires NBIA Data Retriever.) | |
Please contact help@cancerimagingarchive.net with any questions regarding usage. |
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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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| 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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| Wee, L., Aerts, H., Kalendralis, P., & Dekker, A. (2020). 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 |
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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. Journal of Digital Imaging, 26(6), 1045–1057. https://doi.org/10.1007/s10278-013-9622-7 |
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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., 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. |
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| Version 2 (Current): Updated 2021/10/28| 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) | |
The authors of this dataset agreed to change the license to permit commercial use. The actual dataset remains unchanged. Version 1: Updated 2020/02/13| 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) | |
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