Mammography with deep learning for breast cancer detection
X-ray mammography is currently considered the golden standard method for breast cancer screening, however, it has limitations in terms of sensitivity and specificity. With the rapid advancements in deep learning techniques, it is possible to customize mammography for each patient, providing more acc...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2024-02-01
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| Series: | Frontiers in Oncology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2024.1281922/full |
| _version_ | 1797316774668009472 |
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| author | Lulu Wang |
| author_facet | Lulu Wang |
| author_sort | Lulu Wang |
| collection | DOAJ |
| description | X-ray mammography is currently considered the golden standard method for breast cancer screening, however, it has limitations in terms of sensitivity and specificity. With the rapid advancements in deep learning techniques, it is possible to customize mammography for each patient, providing more accurate information for risk assessment, prognosis, and treatment planning. This paper aims to study the recent achievements of deep learning-based mammography for breast cancer detection and classification. This review paper highlights the potential of deep learning-assisted X-ray mammography in improving the accuracy of breast cancer screening. While the potential benefits are clear, it is essential to address the challenges associated with implementing this technology in clinical settings. Future research should focus on refining deep learning algorithms, ensuring data privacy, improving model interpretability, and establishing generalizability to successfully integrate deep learning-assisted mammography into routine breast cancer screening programs. It is hoped that the research findings will assist investigators, engineers, and clinicians in developing more effective breast imaging tools that provide accurate diagnosis, sensitivity, and specificity for breast cancer. |
| first_indexed | 2024-03-08T03:23:16Z |
| format | Article |
| id | doaj.art-2f31509d92eb4624a860e253fff20c33 |
| institution | Directory Open Access Journal |
| issn | 2234-943X |
| language | English |
| last_indexed | 2024-03-08T03:23:16Z |
| publishDate | 2024-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Oncology |
| spelling | doaj.art-2f31509d92eb4624a860e253fff20c332024-02-12T04:45:19ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2024-02-011410.3389/fonc.2024.12819221281922Mammography with deep learning for breast cancer detectionLulu WangX-ray mammography is currently considered the golden standard method for breast cancer screening, however, it has limitations in terms of sensitivity and specificity. With the rapid advancements in deep learning techniques, it is possible to customize mammography for each patient, providing more accurate information for risk assessment, prognosis, and treatment planning. This paper aims to study the recent achievements of deep learning-based mammography for breast cancer detection and classification. This review paper highlights the potential of deep learning-assisted X-ray mammography in improving the accuracy of breast cancer screening. While the potential benefits are clear, it is essential to address the challenges associated with implementing this technology in clinical settings. Future research should focus on refining deep learning algorithms, ensuring data privacy, improving model interpretability, and establishing generalizability to successfully integrate deep learning-assisted mammography into routine breast cancer screening programs. It is hoped that the research findings will assist investigators, engineers, and clinicians in developing more effective breast imaging tools that provide accurate diagnosis, sensitivity, and specificity for breast cancer.https://www.frontiersin.org/articles/10.3389/fonc.2024.1281922/fullbreast cancerclassificationX-ray mammographyartificial intelligencemachine learningdeep learning |
| spellingShingle | Lulu Wang Mammography with deep learning for breast cancer detection Frontiers in Oncology breast cancer classification X-ray mammography artificial intelligence machine learning deep learning |
| title | Mammography with deep learning for breast cancer detection |
| title_full | Mammography with deep learning for breast cancer detection |
| title_fullStr | Mammography with deep learning for breast cancer detection |
| title_full_unstemmed | Mammography with deep learning for breast cancer detection |
| title_short | Mammography with deep learning for breast cancer detection |
| title_sort | mammography with deep learning for breast cancer detection |
| topic | breast cancer classification X-ray mammography artificial intelligence machine learning deep learning |
| url | https://www.frontiersin.org/articles/10.3389/fonc.2024.1281922/full |
| work_keys_str_mv | AT luluwang mammographywithdeeplearningforbreastcancerdetection |