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An Online Mammography Database with Biopsy Confirmed Types
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...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9992520/ https://www.ncbi.nlm.nih.gov/pubmed/36882402 http://dx.doi.org/10.1038/s41597-023-02025-1 |
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author | Cai, Hongmin Wang, Jinhua Dan, Tingting Li, Jiao Fan, Zhihao Yi, Weiting Cui, Chunyan Jiang, Xinhua Li, Li |
author_facet | Cai, Hongmin Wang, Jinhua Dan, Tingting Li, Jiao Fan, Zhihao Yi, Weiting Cui, Chunyan Jiang, Xinhua Li, Li |
author_sort | Cai, Hongmin |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9992520 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-99925202023-03-09 An Online Mammography Database with Biopsy Confirmed Types Cai, Hongmin Wang, Jinhua Dan, Tingting Li, Jiao Fan, Zhihao Yi, Weiting Cui, Chunyan Jiang, Xinhua Li, Li Sci Data Data Descriptor 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. Nature Publishing Group UK 2023-03-07 /pmc/articles/PMC9992520/ /pubmed/36882402 http://dx.doi.org/10.1038/s41597-023-02025-1 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Data Descriptor Cai, Hongmin Wang, Jinhua Dan, Tingting Li, Jiao Fan, Zhihao Yi, Weiting Cui, Chunyan Jiang, Xinhua Li, Li An Online Mammography Database with Biopsy Confirmed Types |
title | An Online Mammography Database with Biopsy Confirmed Types |
title_full | An Online Mammography Database with Biopsy Confirmed Types |
title_fullStr | An Online Mammography Database with Biopsy Confirmed Types |
title_full_unstemmed | An Online Mammography Database with Biopsy Confirmed Types |
title_short | An Online Mammography Database with Biopsy Confirmed Types |
title_sort | online mammography database with biopsy confirmed types |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9992520/ https://www.ncbi.nlm.nih.gov/pubmed/36882402 http://dx.doi.org/10.1038/s41597-023-02025-1 |
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