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Cai H, Wang J, Dan T, Li J, Fan Z, Yi W, Cui C, Jiang X, Li L. An Online Mammography Database with Biopsy Confirmed Types. Sci Data 2023; 10:123. [PMID: 36882402 PMCID: PMC9992520 DOI: 10.1038/s41597-023-02025-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Accepted: 02/15/2023] [Indexed: 03/09/2023] Open
Abstract
Breast carcinoma is the second largest cancer in the world among women. Early detection of breast cancer has been shown to increase the survival rate, thereby significantly increasing patients' lifespan. Mammography, a noninvasive imaging tool with low cost, is widely used to diagnose breast disease at an early stage due to its high sensitivity. Although some public mammography datasets are useful, there is still a lack of open access datasets that expand beyond the white population as well as missing biopsy confirmation or with unknown molecular subtypes. To fill this gap, we build a database containing two online breast mammographies. The dataset named by Chinese Mammography Database (CMMD) contains 3712 mammographies involved 1775 patients, which is divided into two branches. The first dataset CMMD1 contains 1026 cases (2214 mammographies) with biopsy confirmed type of benign or malignant tumors. The second dataset CMMD2 includes 1498 mammographies for 749 patients with known molecular subtypes. Our database is constructed to enrich the diversity of mammography data and promote the development of relevant fields.
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Affiliation(s)
- Hongmin Cai
- School of Computer Science and Engineering, South China University of Technology, Guangzhou, 510006, China.
| | - Jinhua Wang
- Medical Imaging Center, Shenzhen Hospital, Southern Medical University, Shenzhen, 510515, China
- The Third of Clinical Medicine, Southern Medical University, Shenzhen, 510515, China
| | - Tingting Dan
- School of Computer Science and Engineering, South China University of Technology, Guangzhou, 510006, China
| | - Jiao Li
- Department of Medical Imaging, Collaborative Innovation Center for Cancer Medicine, State Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Guangzhou, 510060, China
| | - Zhihao Fan
- School of Computer Science and Engineering, South China University of Technology, Guangzhou, 510006, China
| | - Weiting Yi
- School of Computer Science and Engineering, South China University of Technology, Guangzhou, 510006, China
| | - Chunyan Cui
- Department of Medical Imaging, Collaborative Innovation Center for Cancer Medicine, State Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Guangzhou, 510060, China
| | - Xinhua Jiang
- Department of Medical Imaging, Collaborative Innovation Center for Cancer Medicine, State Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Guangzhou, 510060, China
| | - Li Li
- Department of Medical Imaging, Collaborative Innovation Center for Cancer Medicine, State Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Guangzhou, 510060, China.
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