DRO-Toolkit | Stanford DRO Toolkit: Digital Reference Objects for Standardization of Radiomic Features
DOI: 10.7937/T062-8262 | Page Accessibility: Public | Collection
| Location | Species | Subjects | Data Types | Cancer Types | Size | Status | Updated |
|---|---|---|---|---|---|---|---|
| Phantom | Human | 32 | CT, SEG | Phantom | Public, Complete | 2023/09/13 |
Summary
This is a sample collection of synthetic 3D Digital Reference Objects (DROs) intended for standardization of quantitative imaging feature extraction pipelines. We have developed a software toolkit for the creation of DROs with customizable size, shape, intensity, texture, and margin sharpness values. Using user-supplied input parameters, these objects are defined mathematically as continuous functions, discretized, and then saved as DICOM objects. This collection includes objects with a range of values for the various feature categories and many combinations of these categories.
Acknowledgements
We would like to acknowledge the individuals and institutions that contributed to the development and creation of these digital reference objects:
- Stanford University School of Medicine, Stanford, California, USA - Akshay Jaggi B.S. and Sandy Napel PhD from the Department of Radiology
- University of California, Los Angeles School of Medicine, Los Angeles, California, USA - Michael McNitt-Gray PhD from the Department of Radiology
- The University of Western Ontario, Department of Medical Biophysics - Sarah Mattonen PhD
- The National Cancer Institute Quantitative Imaging Network (QIN)
Data Access
Click the Versions tab for more info about data releases.
| Title | Data Type | Format | Access Points | License | |||
|---|---|---|---|---|---|---|---|
| Images and Segmentations | CT, SEG | DICOM | Requires NBIA Data Retriever |
32 | 64 | 9,632 | CC BY 3.0 |
| Images and Segmentations | NIFTI and ZIP | CC BY 3.0 |
Additional Resources for this Dataset
The NCI Cancer Research Data Commons (CRDC) provides access to additional data and a cloud-based data science infrastructure that connects data sets with analytics tools to allow users to share, integrate, analyze, and visualize cancer research data.
- Imaging Data Commons (IDC) (Imaging Data)
Third Party Analyses of this Dataset
TCIA encourages the community to publish your analyses of our datasets. Below is a list of such third party analyses published using this Collection:
Detailed Description
The detailed description table applies to the DICOM files only. The NIfTI data is not included in this table.
Citations & Data Usage Policy
Data Citation |
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Jaggi, A., Mattonen, S. A., McNitt-Gray, M., & Napel, S. (2020). Stanford DRO Toolkit: Digital Reference Objects for Standardization of Radiomic Features (Version 1) [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/T062-8262 |
Publication Citation |
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Jaggi, A., Mattonen, S. A., McNitt-Gray, M., & Napel, S. (2020). Stanford DRO Toolkit: Digital Reference Objects for Standardization of Radiomic Features. In Tomography (Vol. 6, Issue 2, pp. 111–117). MDPI AG. https://doi.org/10.18383/j.tom.2019.00030 |
TCIA Citation |
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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. In Journal of Digital Imaging (Vol. 26, Issue 6, pp. 1045–1057). Springer Science and Business Media LLC. https://doi.org/10.1007/s10278-013-9622-7 |
Other Publications Using This Data
TCIA maintains a list of publications which leverage TCIA data. If you have a manuscript you’d like to add please contact the TCIA Helpdesk.