Localtab |
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active | true |
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title | Data Access |
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| Data AccessData Type | Download all or Query/Filter |
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Images (DICOM, XX.X GB) | (Download requires the NBIA Data Retriever) | Clinical data (CSV) | | Inclusion-Exclusion criteria (pdf) | Tcia button generator |
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url | https://wiki.cancerimagingarchive.net/download/attachments/70230508/CMMD_Inclusion_Exclusion_criteria.pdf |
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Click the Versions tab for more info about data releases. Please contact help@cancerimagingarchive.net with any questions regarding usage. |
Localtab |
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title | Detailed Description |
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| Detailed DescriptionImage Statistics |
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Modalities | MG | Number of Patients | 25241775 | Number of Studies | 25241775 | Number of Series | 25241775 | Number of Images | 37285202 | Images Size (GB) | 22.9 GB |
- Mammography images were collected in .TIFF format.
- Clinical data are saved in .CSV format
- laterality and view in a CSV to facilitate our conversion to DICOM
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Localtab |
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title | Citations & Data Usage Policy |
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| Citations & Data Usage Policy Tcia license 4 international |
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Info |
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| Cui, Chunyan; Li Li; Cai, Hongmin; Fan, Zhihao; Zhang, Ling; Dan, Tingting; Li, Jiao; Wang, Jinghua. (2021) The Chinese Mammography Database (CMMD): An online mammography database with biopsy confirmed types for machine diagnosis of breast. The Cancer Imaging Archive. DOI: https://doi.org/10.7937/tcia.eqde-4b16 DOI IS IN DRAFT MODE WITHOUT AN ABSTRACT 3/12/21 -QUESTIONS: Do we need to acknowledge DClunie's work to convert TIF to DICOM and how is that acknowledged, is the abstract exactly what this group wants to see? |
Info |
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title | Publication Citation |
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| Cai, H., Huang, Q., Rong, W., Song, Y., Li, J., Wang, J., Chen, J., & Li, L. (2019). Breast Microcalcification Diagnosis Using Deep Convolutional Neural Network from Digital Mammograms. Computational and Mathematical Methods in Medicine, 2019, 1–10. https://doi.org/10.1155/2019/2717454
Wang, J., Yang, X., Cai, H., Tan, W., Jin, C., & Li, L. (2016). Discrimination of Breast Cancer with Microcalcifications on Mammography by Deep Learning. Scientific Reports, 6(1). https://doi.org/10.1038/srep27327 |
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. (2013). The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository. Journal of Digital Imaging, 26(6), 1045–1057. https://doi.org/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. |
Localtab |
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| Version 1 (Current): Updated yyyy/mm/ddData Type | Download all or Query/Filter |
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Images (DICOM, xx22.x 9 GB) | |
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