Application of machine learning method in optical molecular imaging: a review

作     者：Yu AN Hui MENG Yuan GAO Tong TONG Chong ZHANG Kun WANG Jie TIAN Yu AN;Hui MENG;Yuan GAO;Tong TONG;Chong ZHANG;Kun WANG;Jie TIAN

作者机构：CAS Key Laboratory of Molecular Imaging Beijing Key Laboratory of Molecular ImagingThe State Key Laboratory of Management and Control for Complex SystemsInstitute of Automation Chinese Academy of Sciences Beijing Advanced Innovation Center for Big Data-Based Precision Medicine School of MedicineBeihang University University of Chinese Academy of Sciences 

出 版 物：《Science China(Information Sciences)》 (中国科学:信息科学(英文版))

年 卷 期：2020年第63卷第1期

页      面：5-20页

核心收录：

学科分类：0831[工学-生物医学工程（可授工学、理学、医学学位）] 100207[医学-影像医学与核医学] 070207[理学-光学] 1002[医学-临床医学] 07[理学] 08[工学] 080203[工学-机械设计及理论] 1010[医学-医学技术（可授医学、理学学位）] 0802[工学-机械工程] 0803[工学-光学工程] 0702[理学-物理学] 10[医学] 

基　　金：supported by Ministry of Science and Technology of China (Grant Nos. 2018YFC0910602, 2017YFA0205200, 2017YFA0700401, 2016YFA0100902, 2016YFC0103702) National Natural Science Foundation of China (Grant Nos. 61901472, 61671449, 81227901, 81527805) the Strategic Priority Research Program of Chinese Academy of Sciences (Grant Nos. XDB32030200, XDB01030200) Chinese Academy of Sciences (Grant Nos. GJJSTD20170004, YJKYYQ20180048, KFJ-STS-ZDTP-059, QYZDJ-SSW-JSC005) Beijing Municipal Science & Technology Commission (Grant Nos. Z161100002616022, Z171100000117023) General Financial Grant from the China Postdoctoral Science Foundation (Grant No. 2017M620952) 

主　　题：optical molecular imaging machine learning artificial intelligence 

摘      要：Optical molecular imaging(OMI) is an imaging technology that uses an optical signal, such as near-infrared light, to detect biological tissue in organisms. Because of its specific and sensitive imaging performance, it is applied in both preclinical research and clinical surgery. However, it requires heavy data analysis and a complex mathematical model of tomographic imaging. In recent years, machine learning(ML)-based artificial intelligence has been used in different fields because of its ability to perform powerful data processing. Its analytical capability for processing complex and large data provides a feasible scheme for the requirement of OMI. In this paper, we review ML-based methods applied in different OMI modalities.