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| 医学影像人工智能：进展和未来 | |
| 引用本文： | 刘再毅,石镇维. 医学影像人工智能：进展和未来[J]. 国际医学放射学杂志, 2023, 46(1): 1-4. DOI: 10.19300/j.2023.S20494 |
| 作者姓名： | 刘再毅 石镇维 |
| 作者单位： | 1 广东省人民医院/广东省医学科学院放射科,广州510080 2 广东省医学影像智能分析与应用实验室 3 广东省心血管研究所 |
| 基金项目： | 国家自然科学基金(U22A20345);国家自然科学基金(82102034);广东省科技计划项目(2022B1212010011);中国博士后科学基金资助项目(2022M710843) |
| 摘 要： | 基于医学影像构建的人工智能（AI）系统已在疾病诊疗方面展现出了巨大的应用潜能。然而,距离临床应用仍面临着诸多挑战。就医学影像数据标准化、模型泛化性、生物学可解释性、医学数据孤岛与隐私保护等方面来探讨医学影像AI的进展与未来。在未来的工作中,有必要引入更多新技术、新理论,构建高效、泛化性强的医学影像AI标准化数据库,积极推进医学影像AI在疾病诊疗领域的临床应用。 |
| 关 键 词： | 医学影像 人工智能 影像组学 联邦学习 标准化数据库 |
| 收稿时间： | 2022-11-30 |
Artificial intelligence in medical imaging: progress and perspectives |
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| LIU Zaiyi,SHI Zhenwei. Artificial intelligence in medical imaging: progress and perspectives[J]. International Journal of Medical Radiology, 2023, 46(1): 1-4. DOI: 10.19300/j.2023.S20494 | |
| Authors: | LIU Zaiyi SHI Zhenwei |
| Affiliation: | 1 Department of Radiology, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China 2 Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application 3 Guangdong Cardiovascular Institute |
| Abstract: | Artificial intelligence in medical imaging has shown huge applicable potentiallity in disease diagnosis and prognosis. However, it remains many challenges impeding its’ application in clinical practice. In this study, we investigated the progress and perspectives of artificial intelligence in medical imaging, especially the challenges such as data standardization, model generalizability, biological interpretation, and privacy protection. In future, it is necessary to introduce new technologies and principles to build standardized data repository with high efficiency and generalizability, in order to promote the clinical application of artificial intelligence in the field of disease diagnosis and treatment. |
| Keywords: | Medical imaging Artificial intelligence Radiomics Federated learning Data standardization |
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