Artificial intelligence in breast imaging: Current situation and clinical challenges

Author:

You Chao12,Shen Yiyuan12,Sun Shiyun12,Zhou Jiayin12,Li Jiawei12,Su Guanhua23,Michalopoulou Eleni4,Peng Weijun12,Gu Yajia12,Guo Weisheng5ORCID,Cao Heqi6

Affiliation:

1. Department of Radiology Fudan University Shanghai Cancer Center Shanghai China

2. Department of Oncology Shanghai Medical College Fudan University Shanghai China

3. Department of Breast Surgery Key Laboratory of Breast Cancer in Shanghai Fudan University Shanghai Cancer Center Shanghai China

4. Technical Services Team University of Nottingham Nottingham UK

5. Department of Minimally Invasive Interventional Radiology Key Laboratory of Molecular Target and Clinical Pharmacology School of Pharmaceutical Sciences and The Second Affiliated Hospital Guangzhou Medical University Guangzhou China

6. Department of Health Sciences National Natural Science Foundation of China Beijing China

Abstract

AbstractBreast cancer ranks among the most prevalent malignant tumours and is the primary contributor to cancer‐related deaths in women. Breast imaging is essential for screening, diagnosis, and therapeutic surveillance. With the increasing demand for precision medicine, the heterogeneous nature of breast cancer makes it necessary to deeply mine and rationally utilize the tremendous amount of breast imaging information. With the rapid advancement of computer science, artificial intelligence (AI) has been noted to have great advantages in processing and mining of image information. Therefore, a growing number of scholars have started to focus on and research the utility of AI in breast imaging. Here, an overview of breast imaging databases and recent advances in AI research are provided, the challenges and problems in this field are discussed, and then constructive advice is further provided for ongoing scientific developments from the perspective of the National Natural Science Foundation of China.

Funder

National Natural Science Foundation of China

Publisher

Wiley

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3