Zhang Chong, Gu Jionghui, Zhu Yangyang, Meng Zheling, Tong Tong, Li Dongyang, Liu Zhenyu, Du Yang, Wang Kun, Tian Jie
Department of Big Data Management and Application, School of International Economics and Management, Beijing Technology and Business University, Beijing 100048, China.
CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.
Precis Clin Med. 2021 Dec 4;4(4):271-286. doi: 10.1093/pcmedi/pbab026. eCollection 2021 Dec.
Medical imaging provides a comprehensive perspective and rich information for disease diagnosis. Combined with artificial intelligence technology, medical imaging can be further mined for detailed pathological information. Many studies have shown that the macroscopic imaging characteristics of tumors are closely related to microscopic gene, protein and molecular changes. In order to explore the function of artificial intelligence algorithms in in-depth analysis of medical imaging information, this paper reviews the articles published in recent years from three perspectives: medical imaging analysis method, clinical applications and the development of medical imaging in the direction of pathological molecular prediction. We believe that AI-aided medical imaging analysis will be extensively contributing to precise and efficient clinical decision.
医学影像为疾病诊断提供了全面的视角和丰富的信息。结合人工智能技术，医学影像可进一步挖掘出详细的病理信息。许多研究表明，肿瘤的宏观影像特征与微观基因、蛋白质和分子变化密切相关。为了探讨人工智能算法在医学影像信息深度分析中的作用，本文从医学影像分析方法、临床应用以及医学影像在病理分子预测方向的发展三个角度对近年来发表的文章进行综述。我们认为，人工智能辅助的医学影像分析将为精准高效的临床决策做出广泛贡献。
