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

doi:10.1007/s11432-019-2708-1

	Application of machine learning method in optical molecular imaging: a review
	An, Yu 1; Meng, Hui1,2 ; Gao, Yuan1,2 ; Tong, Tong1,2 ; Zhang, Chong1,2 ; Wang, Kun1 ; Tian, Jie 1,3
发表期刊	SCIENCE CHINA-INFORMATION SCIENCES
ISSN	1674-733X
	2020
卷号	63 期号:1 页码:16
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.
关键词	optical molecular imaging machine learning artificial intelligence
DOI	10.1007/s11432-019-2708-1
关键词[WOS]	CONVOLUTIONAL NEURAL-NETWORKS ; BIOLUMINESCENCE TOMOGRAPHY ; COHERENCE TOMOGRAPHY ; PHOTOACOUSTIC TOMOGRAPHY ; RECONSTRUCTION ALGORITHM ; LUMEN SEGMENTATION ; FLUORESCENCE ; CANCER ; QUANTIFICATION ; DIAGNOSIS
收录类别	SCI
语种	英语
资助项目	General Financial Grant from the China Postdoctoral Science Foundation[2017M620952] ; Strategic Priority Research Program of Chinese Academy of Sciences[XDB01030200] ; Strategic Priority Research Program of Chinese Academy of Sciences[XDB32030200] ; National Natural Science Foundation of China[61901472] ; Ministry of Science and Technology of China[2016YFC0103702] ; Ministry of Science and Technology of China[2018YFC0910602] ; Ministry of Science and Technology of China[2016YFA0100902] ; Chinese Academy of Sciences[YJKYYQ20180048] ; Chinese Academy of Sciences[KFJ-STS-ZDTP-059] ; Ministry of Science and Technology of China[2017YFA0700401] ; Beijing Municipal Science & Technology Commission[Z171100000117023] ; Chinese Academy of Sciences[QYZDJ-SSW-JSC005] ; Chinese Academy of Sciences[GJJSTD20170004] ; National Natural Science Foundation of China[61671449] ; Ministry of Science and Technology of China[2017YFA0205200] ; Beijing Municipal Science & Technology Commission[Z161100002616022] ; National Natural Science Foundation of China[81527805] ; National Natural Science Foundation of China[81227901] ; National Natural Science Foundation of China[81227901] ; National Natural Science Foundation of China[81527805] ; Beijing Municipal Science & Technology Commission[Z161100002616022] ; Ministry of Science and Technology of China[2017YFA0205200] ; National Natural Science Foundation of China[61671449] ; Chinese Academy of Sciences[GJJSTD20170004] ; Chinese Academy of Sciences[QYZDJ-SSW-JSC005] ; Beijing Municipal Science & Technology Commission[Z171100000117023] ; Ministry of Science and Technology of China[2017YFA0700401] ; Chinese Academy of Sciences[KFJ-STS-ZDTP-059] ; Chinese Academy of Sciences[YJKYYQ20180048] ; Ministry of Science and Technology of China[2016YFA0100902] ; Ministry of Science and Technology of China[2018YFC0910602] ; Ministry of Science and Technology of China[2016YFC0103702] ; National Natural Science Foundation of China[61901472] ; Strategic Priority Research Program of Chinese Academy of Sciences[XDB32030200] ; Strategic Priority Research Program of Chinese Academy of Sciences[XDB01030200] ; General Financial Grant from the China Postdoctoral Science Foundation[2017M620952]
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Information Systems ; Engineering, Electrical & Electronic
WOS记录号	WOS:000513494600001
出版者	SCIENCE PRESS
七大方向——子方向分类	医学影像处理与分析
引用统计	被引频次：6[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/28599
专题	中国科学院分子影像重点实验室
通讯作者	Tian, Jie
作者单位	1.Chinese Acad Sci, Beijing Key Lab Mol Imaging, State Key Lab Management & Control Complex Syst, CAS Key Lab Mol Imaging,Inst Automat, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 3.Beihang Univ, Beijing Adv Innovat Ctr Big Data Based Precis Med, Sch Med, Beijing 100191, Peoples R China
推荐引用方式 GB/T 7714	An, Yu,Meng, Hui,Gao, Yuan,et al. Application of machine learning method in optical molecular imaging: a review[J]. SCIENCE CHINA-INFORMATION SCIENCES,2020,63(1):16.
APA	An, Yu.,Meng, Hui.,Gao, Yuan.,Tong, Tong.,Zhang, Chong.,...&Tian, Jie.(2020).Application of machine learning method in optical molecular imaging: a review.SCIENCE CHINA-INFORMATION SCIENCES,63(1),16.
MLA	An, Yu,et al."Application of machine learning method in optical molecular imaging: a review".SCIENCE CHINA-INFORMATION SCIENCES 63.1(2020):16.

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