Summary
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This collection consists of 251 CT scans of Credence Cartridge Radiomic (CCR) phantom. This texture phantom was developed to investigate the feature robustness in the emerging field of radiomics. This phantom dataset was acquired on 4-8 CT scanners using a set of imaging parameters (e.g., reconstruction Field of View, Slice thickness, reconstruction kernels, mAs, and Pitch). A controlled scanning approach was employed to assess the variability in radiomic features due to each imaging parameter. This dataset will be useful to radiomic research community to identify a subset of robust radiomic features and for establishing the ground truths for future clinical investigations.
This Phantom dataset can be used for Feature variability assessment due to CT imaging parameters. These phantom scans can be used to identify a subset of robust radiomic features for future clinical investigations. Using this dataset, the numerical values of radiomic features can be cross-validated by other research groups using their own feature extraction tools.
Acknowledgements
This dataset was submitted by Dr. Eduardo G. Moros and Dr. M Shafiq ul Hassan, USF. Special thanks to Moffitt Cancer Center where data were acquired.
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| title | Data Access |
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| Type | Download all or Query/Filter | License |
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| Images (DICOM, 30.5GB) |
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| url | https://wiki.cancerimagingarchive.net/download/attachments/39879218/CC-Radiomics-Phantom-2-NBIA-manifest.tcia?version=1&modificationDate=1551287978550&api=v2 |
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| url | https://nbia.cancerimagingarchive.net/nbia-search/?MinNumberOfStudiesCriteria=1&CollectionCriteria=CC-Radiomics-Phantom-2 |
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Additional Resources for this Dataset
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| title | Detailed Description |
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| Detailed Description |
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Patients | 251 | Number of Studies | 251 | Number of Series | 251 | Number of Images | 57,839 | | Images Size (GB) | 30.5 |
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| title | Citations & Data Usage Policy |
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| Info |
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| Shafiq ul Hassan M, Zhang G, Latifi K, Ullah G, Gillies R, Moros E. Credence Cartridge Radiomics Phantom CT Scans with Controlled Scanning Approach. 2018. |
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| title | Publication Citation |
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| Muhammad Shafiq ul Hassan, Geoffrey Zhang, Kujtim Latifi, Ghanim Ullah, Robert Gillies, Eduardo G. Moros. (2019) Computed Tomography Texture Phantom Dataset for Evaluating the Impact of CT Imaging Parameters on Radiomic Features. (link to |
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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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Other Publications Using This Data
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Additional Publication Resources:The Collection authors suggest the below will give context to this dataset: Shafiq ul Hassan M, Latifi K, Zhang G, Ullah G, Gillies R and Moros E. (2018) Voxel size and gray level normalization of CT radiomic features in lung cancer patients. Scientific Reports. Shafiq ul Hassan M, Zhang G, Hunt D, Latifi K, Ullah G, Gillies R and Moros E,
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spectra’, J. Med. Imag. 5(1), 011013 (2017). DOI: 10.1117/1.JMI.5.1.011013 Shafiq ul Hassan M, Zhang G, Latifi K, Ullah G, Hunt D, Balagurunathan Y, Abdullah M, Schabath M, Goldgof D, Mackin D, Court L, Gillies R and Moros E. (2017) Intrinsic dependencies of CT radiomic features on voxel size and number of gray levels. Med. Phys. 44(3), p-1050-1062 . Paul R, Shafiq ul Hassan M, Moros E, Gillies R, Hall L, Goldgof D. (2018) Stability of deep features across CT scanners and Field Of View (FOV) using a physical phantom. Proc SPIE Medical Imaging Conference, February 2018, Texas, USA
Other Publications Using This DataTCIA maintains a list of publications which leverage our data. If you have a manuscript you'd like to add please contact TCIA's Helpdesk. |
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| Data Type | Download all or Query/Filter |
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| Images (DICOM, 30.5GB) |
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| url | https://wiki.cancerimagingarchive.net/download/attachments/39879218/CC-Radiomics-Phantom-2-NBIA-manifest.tcia?version=1&modificationDate=1551287978550&api=v2 |
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| label | Search |
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| url | https://nbia.cancerimagingarchive.net/nbia-search/?MinNumberOfStudiesCriteria=1&CollectionCriteria=CC-Radiomics-Phantom-2 |
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