The Cancer Imaging Archive (TCIA) Public Access

Space shortcuts

Child pages
  • Credence Cartridge Radiomics Phantom CT Scans with Controlled Scanning Approach (CC-Radiomics-Phantom-2)

Versions Compared

Old Version 48

changes.mady.by.user Tracy Nolan

Saved on

compared with

New Version 49

changes.mady.by.user Tracy Nolan

Saved on

Key

  • This line was added.
  • This line was removed.
  • Formatting was changed.

...

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.

Localtab Group


Localtab
activetrue
titleData Access

Data Access

Data TypeDownload all or Query/FilterLicense
Images (DICOM, 30.5GB)


Tcia button generator
urlhttps://wiki.cancerimagingarchive.net/download/attachments/39879218/CC-Radiomics-Phantom-2-NBIA-manifest.tcia?version=1&modificationDate=1551287978550&api=v2



Tcia button generator
labelSearch
urlhttps://nbia.cancerimagingarchive.net/nbia-search/?MinNumberOfStudiesCriteria=1&CollectionCriteria=CC-Radiomics-Phantom-2


(Download requires the NBIA Data Retriever)

Tcia cc by 3

Click the Versions tab for more info about data releases.


Localtab
titleDetailed Description

Detailed Description

Image Statistics


Modalities

CT

Number of Patients

251

Number of Studies

251

Number of Series

251

Number of Images

57,839

Images Size (GB)30.5



Localtab
titleCitations & Data Usage Policy

Citations & Data Usage Policy 

Tcia limited license policy

Info
titleData Citation

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. DOI: http://doi.org/10.7937/TCIA.2019.4l24tz5g


Info
titlePublication Citation

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 attached PDF)


Info
titleTCIA Citation

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

Other Publications Using This Data

Additional Publication Resources:

The

data submitters

Collection authors suggest the

following manuscripts may be useful to the researchers utilizing this collection

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, ‘Accounting for reconstruction kernel-induced variability in CT radiomic features using noise power 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 Data

TCIA maintains a list of publications which leverage our data. If you have a manuscript you'd like to add please contact TCIA's Helpdesk.


Localtab
titleVersions

Version 1 (Current):  2019/02/27

Data TypeDownload all or Query/Filter
Images (DICOM, 30.5GB)


Tcia button generator
urlhttps://wiki.cancerimagingarchive.net/download/attachments/39879218/CC-Radiomics-Phantom-2-NBIA-manifest.tcia?version=1&modificationDate=1551287978550&api=v2



Tcia button generator
labelSearch
urlhttps://nbia.cancerimagingarchive.net/nbia-search/?MinNumberOfStudiesCriteria=1&CollectionCriteria=CC-Radiomics-Phantom-2






...