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Breast cancer is among the most common cancers and a common cause of death among women. Over 39 million breast cancer screening exams are performed every year and are among the most common radiological tests. This creates a high need for accurate image interpretation. Machine learning has shown promise in interpretation of medical images. However, limited data for training and validation remains an issue.
Here, we share a curated dataset of digital breast tomosynthesis images that includes normal, actionable, biopsy-proven benign, and biopsy-proven cancer cases. The dataset contains four components: (1) DICOM images, (2) a spreadsheet indicating which group each case belongs to, and (3) annotation boxes. A detailed description of this dataset can be found in the following paper:
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title | Publication Citation |
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Buda, A. Saha, R. Walsh, S. Ghate, N. Li, A. Święcicki, J. Y. Lo, M. A. Mazurowski, Detection of masses and architectural distortions in digital breast tomosynthesis: a publicly available dataset of 5,060 patients and a deep learning model. arXiv preprint arXiv:2011.07995. |
Please reference this paper if you use this dataset. Please note that version Version 1 of the dataset contains only a subset of all data described in the paper above. More data will be share in subsequent versions.The dataset contains four components: (1) DICOM images, (2) a spreadsheet indicating which group each case belongs to, and (3) annotation boxes.
Acknowledgements
We would like to acknowledge the individuals and institutions that have provided data for this collection:
Duke University Hospital/Duke University, Durham, NC, USA
We would like to acknowledge all those who contributed to the curation of this dataset
This work was supported by a grant from the NIH: 1 R01 EB021360 (PI: Mazurowski).
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title | Data Access |
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| Data AccessClick the Download button to save a ".tcia" manifest file to your computer, which you must open with the NBIA Data Retriever . Click the Search button to open our Data Portal, where you can browse the data collection and/or download a subset of its contents. Data Type | Download all or Query/Filter |
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Images (DICOM, XX.X GB) DBT | Tcia button generator |
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url | https://wiki.cancerimagingarchive.net/download/attachments/64685580/DBT-Challenge-Train.TCIA?api=v2 |
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(Search button will not work until the data are ready to be released) | Annotations (csv) | Tcia button generator |
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url | https://wiki.cancerimagingarchive.net/download/attachments/64685580/Duke%20Breast%20DBT%20boxes-train.csv?api=v2 |
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| Labels (csv) | Tcia button generator |
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url | https://wiki.cancerimagingarchive.net/download/attachments/64685580/Duke%20Breast%20DBT%20labels-train.csv?api=v2 |
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| Click the Versions tab for more info about data releases. |
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title | Detailed Description |
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| Detailed Description | |
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Modalities | DBT | Number of Participants | 693 | Number of Studies | 700 | Number of Series | 2596 | Number of Images | 2596 | Images Size (GB, compressed) | Added when data released |
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title | Citations & Data Usage Policy |
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| Citations & Data Usage PolicyAdd any special restrictions in here. Tcia license 4 international |
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| Buda, M., Saha, A., Li, N., Mazurowski, M.A. (2020). Data from the Breast Cancer Screening DBT. Data from The Cancer Imaging Archive. (2020). http://doi.org (Coming soon). |
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title | Publication Citation |
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| Buda, M., Saha, A., Walsh, R., Ghate, S., Li, N., Święcicki, A., Lo, J.Y., Mazurowski, M.A., Detection of masses and architectural distortions in digital breast tomosynthesis: a publicly available dataset of 5,060 patients and a deep learning model. arXiv preprint https://arxiv.org/abs/2011.07995. |
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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 |
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. |
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| Version 1 (Current): Updated 2020/mm/dd Data Type | Download all or Query/Filter |
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Images (DICOM, XX.X GB) DBT | Tcia button generator |
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url | https://wiki.cancerimagingarchive.net/download/attachments/64685580/DBT-Challenge-Train.TCIA?api=v2 |
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(Requires NBIA Data Retriever .) (Search button will not work until the data is ready to be released) | Annotations (csv) | Tcia button generator |
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url | https://wiki.cancerimagingarchive.net/download/attachments/64685580/Duke%20Breast%20DBT%20boxes-train.csv?api=v2 |
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| Labels (csv) | Tcia button generator |
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url | https://wiki.cancerimagingarchive.net/download/attachments/64685580/Duke%20Breast%20DBT%20labels-train.csv?api=v2 |
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