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Artificial Intelligence in Medical Imaging of the Breast
Artificial intelligence (AI) has invaded our daily lives, and in the last decade, there have been very promising applications of AI in the field of medicine, including medical imaging, in vitro diagnosis, intelligent rehabilitation, and prognosis. Breast cancer is one of the common malignant tumors...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8339920/ https://www.ncbi.nlm.nih.gov/pubmed/34367938 http://dx.doi.org/10.3389/fonc.2021.600557 |
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author | Lei, Yu-Meng Yin, Miao Yu, Mei-Hui Yu, Jing Zeng, Shu-E Lv, Wen-Zhi Li, Jun Ye, Hua-Rong Cui, Xin-Wu Dietrich, Christoph F. |
author_facet | Lei, Yu-Meng Yin, Miao Yu, Mei-Hui Yu, Jing Zeng, Shu-E Lv, Wen-Zhi Li, Jun Ye, Hua-Rong Cui, Xin-Wu Dietrich, Christoph F. |
author_sort | Lei, Yu-Meng |
collection | PubMed |
description | Artificial intelligence (AI) has invaded our daily lives, and in the last decade, there have been very promising applications of AI in the field of medicine, including medical imaging, in vitro diagnosis, intelligent rehabilitation, and prognosis. Breast cancer is one of the common malignant tumors in women and seriously threatens women’s physical and mental health. Early screening for breast cancer via mammography, ultrasound and magnetic resonance imaging (MRI) can significantly improve the prognosis of patients. AI has shown excellent performance in image recognition tasks and has been widely studied in breast cancer screening. This paper introduces the background of AI and its application in breast medical imaging (mammography, ultrasound and MRI), such as in the identification, segmentation and classification of lesions; breast density assessment; and breast cancer risk assessment. In addition, we also discuss the challenges and future perspectives of the application of AI in medical imaging of the breast. |
format | Online Article Text |
id | pubmed-8339920 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-83399202021-08-06 Artificial Intelligence in Medical Imaging of the Breast Lei, Yu-Meng Yin, Miao Yu, Mei-Hui Yu, Jing Zeng, Shu-E Lv, Wen-Zhi Li, Jun Ye, Hua-Rong Cui, Xin-Wu Dietrich, Christoph F. Front Oncol Oncology Artificial intelligence (AI) has invaded our daily lives, and in the last decade, there have been very promising applications of AI in the field of medicine, including medical imaging, in vitro diagnosis, intelligent rehabilitation, and prognosis. Breast cancer is one of the common malignant tumors in women and seriously threatens women’s physical and mental health. Early screening for breast cancer via mammography, ultrasound and magnetic resonance imaging (MRI) can significantly improve the prognosis of patients. AI has shown excellent performance in image recognition tasks and has been widely studied in breast cancer screening. This paper introduces the background of AI and its application in breast medical imaging (mammography, ultrasound and MRI), such as in the identification, segmentation and classification of lesions; breast density assessment; and breast cancer risk assessment. In addition, we also discuss the challenges and future perspectives of the application of AI in medical imaging of the breast. Frontiers Media S.A. 2021-07-22 /pmc/articles/PMC8339920/ /pubmed/34367938 http://dx.doi.org/10.3389/fonc.2021.600557 Text en Copyright © 2021 Lei, Yin, Yu, Yu, Zeng, Lv, Li, Ye, Cui and Dietrich https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Oncology Lei, Yu-Meng Yin, Miao Yu, Mei-Hui Yu, Jing Zeng, Shu-E Lv, Wen-Zhi Li, Jun Ye, Hua-Rong Cui, Xin-Wu Dietrich, Christoph F. Artificial Intelligence in Medical Imaging of the Breast |
title | Artificial Intelligence in Medical Imaging of the Breast |
title_full | Artificial Intelligence in Medical Imaging of the Breast |
title_fullStr | Artificial Intelligence in Medical Imaging of the Breast |
title_full_unstemmed | Artificial Intelligence in Medical Imaging of the Breast |
title_short | Artificial Intelligence in Medical Imaging of the Breast |
title_sort | artificial intelligence in medical imaging of the breast |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8339920/ https://www.ncbi.nlm.nih.gov/pubmed/34367938 http://dx.doi.org/10.3389/fonc.2021.600557 |
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