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| active | true |
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| title | Data Access |
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| Data AccessClick the Download button to save the data.
| Data Type | Download all or Query/Filter |
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Images (NIfTI, zip, 669 MB) MNI MR/Segs (CWRU annotations only) | | Images (NIfTI, zip, 469 MB) SRI MR/Segs (UPenn & CWRU annotations) | | | Subjects' Meta-data (csv, 7 KB) | | Radiomic Features and Reproducibility Evaluation on SRI data (zip, 17.2 MB) | | | Corresponding Original MR Images from Ivy-GAP (130.4 GB) | |
Please contact help@cancerimagingarchive.net with any questions regarding usage. |
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| title | Detailed Description |
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| Detailed DescriptionThe data comprises of expert segmentation labels from each institution (i.e. 34 subjects from both UPenn and CWRU, with a total of 37), along with the corresponding co-registered and skull-stripped structural MRI scans in the space they were created (i.e., SRI for UPenn and MNI for CWRU), and the expert segmentation labels for the 31 common subjects co-registered in the SRI atlas. For brevity, we have included the corresponding SRI and MNI anatomical atlas files that we employed, the complete set of extracted radiomic features per subject for each of the 31 included subjects, along with the parameters used for the radiomic feature extraction and the correlation analysis results for identifying robust radiomic features, and finally, the identified robust radiomic features.
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| title | Citations & Data Usage Policy |
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| Citations & Data Usage Policy| Public collection license |
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| Info |
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| Pati, S., Verma, R., Akbari, H., Bilello, M., Hill, V.B., Sako, C., Correa, R., Beig, N., Venet, L., Thakur, S., Serai, P., Ha, S.M., Blake, G.D., Shinohara, R.T., Tiwari, P., Bakas, S. (2020). Data from the Multi-Institutional Paired Expert Segmentations and Radiomic Features of the Ivy GAP Dataset. DOI: https://doi.org/10.7937/9j41-7d44. |
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| title | Publication Citation |
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| Pati, S., Verma, R., Akbari, H., Bilello, M., Hill, V.B., Sako, C., Correa, R., Beig, N., Venet, L., Thakur, S., Serai, P., Ha, S.M., Blake, G.D., Shinohara, R.T., Tiwari, P., Bakas, S. (2020). Reproducibility analysis of multi-institutional paired expert annotations and radiomic features of the Ivy Glioblastoma Atlas Project (Ivy GAP) dataset. Medical Physics TCIA Special Issue, In Press, 2020. DOI: https://doi.org/10.1002/mp.14556. |
| 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. DOI: 10.1007/s10278-013-9622-7 |
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| title | Grant Acknowledgement |
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| - National Institutes of Health (NIH) under award number NCI:U01CA242871
- Department of Defense (DoD) Peer Reviewed Cancer Research Program (W81XWH-18-1-0404)
- Dana Foundation David Mahoney Neuroimaging Grant, the CCCC Brain Tumor Pilot Award
- CWRU Technology Validation Start-Up Fund (CTP)
- The V Foundation Translational Research Award.
The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH, U.S. Department of Veterans Affairs, the DoD, or the United States Government. |
Other Publications Using This DataTCIA maintains a list of publications which 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 2020/04/14
| Data Type | Download all or Query/Filter |
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Images (NIfTI, zip, 669 MB) MNI MR/Segs (CWRU annotations only) | | Images (NIfTI, zip, 469 MB) SRI MR/Segs (UPenn & CWRU annotations) | | | Subjects' Meta-data (csv, 7 KB) | | Radiomic Features and Reproducibility Evaluation on SRI data (zip, 17.2 MB) | |
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