| 基于深度学习的乳腺X线摄影的临床应用价值 |
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| 引用本文： | 欧阳汝珊,林小慧,马捷.基于深度学习的乳腺X线摄影的临床应用价值[J].国际医学放射学杂志,2021,44(6):673-677. |
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| 作者姓名： | 欧阳汝珊 林小慧 马捷 |
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| 作者单位： | 暨南大学第二临床医学院(深圳市人民医院)放射科,深圳 518020 |
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| 基金项目： | 广东省医学科学技术研究基金项目(2017114221426693) |
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| 摘 要： | 乳腺X线摄影是乳腺癌筛查的有效手段,但具有一定局限性。人工智能（AI）具有提取图像特征并分析的强大能力,是推动未来智能医学影像进步的核心技术。近年来深度学习（DL）在乳腺X线摄影上的应用迅速发展,能够提高医生的工作效率、诊断准确率并降低漏诊率。对基于DL的乳腺X线摄影在乳腺癌筛查、临床诊断及风险评估中的应用价值和发展前景予以综述与展望。
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| 关 键 词： | 深度学习 乳腺癌 乳腺X线摄影 卷积神经网络 |
| 收稿时间： | 2021-01-12 |
Clinical value of deep learning-based mammography |
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| OUYANG Rushan,LIN Xiaohui,MA Jie.Clinical value of deep learning-based mammography[J].International Journal of Medical Radiology,2021,44(6):673-677. |
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| Authors: | OUYANG Rushan LIN Xiaohui MA Jie |
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| Institution: | Department of Radiology, Second Clinical Medical College of Jinan University, Shenzhen People’s Hospital, Shenzhen 518020, China |
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| Abstract: | Mammography is an effective method for breast cancer screening, but there are some limitations. Artificial intelligence (AI) has a powerful ability to extract and analyze image features, and will be the core technology to promote the intelligent medical imaging in the future. In recent years, the application of deep learning technology on mammography is growing rapidly. It can improve doctors’ work efficiency and accuracy, and reduce the false negative rate. This article reviews the value of deep learning based mammography in breast cancer screening, clinical diagnosis and risk assessment, and prospects of this technology. |
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| Keywords: | Deep learning Breast cancer Mammography Convolutional neural networks |
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