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Non model-based bioluminescence tomography using a machine-learning reconstruction strategy
Gao, Yuan1,2; Wang, Kun1,2; An, Yu1,2; Jiang, Shixin1,3; Meng, Hui1,2; Tian, Jie1,2,4
发表期刊OPTICA
ISSN2334-2536
2018-11-20
卷号5期号:11页码:1451-1454
通讯作者Wang, Kun(kun.wang@ia.ac.cn)
摘要Bioluminescence tomography (BLT) is an effective noninvasive molecular imaging modality for in vivo tumor research in small animals. However, the quality of BLT reconstruction is limited by the simplified linear model of photon propagation. Here, we proposed a multilayer perceptron-based inverse problem simulation (IPS) method to improve the quality of in vivo tumor BLT reconstruction. Instead of solving the inverse problem of the simplified linear model of photon propagation, the IPS method directly fits the nonlinear relationship between an object surface optical density and its internal bioluminescent source. Both simulation and orthotopic glioma BLT reconstruction experiments demonstrated that IPS greatly improved the reconstruction quality compared with the conventional approach. (C) 2018 Optical Society of America under the terms of the OSA Open Access Publishing Agreement
DOI10.1364/OPTICA.5.001451
关键词[WOS]LIGHT ; REGULARIZATION ; REGISTRATION ; INFORMATION ; ALGORITHM ; ACCURACY
收录类别SCI
语种英语
资助项目National Natural Science Foundation of China (NSFC)[61671449] ; National Natural Science Foundation of China (NSFC)[81227901] ; National Natural Science Foundation of China (NSFC)[81527805] ; Ministry of Science and Technology of the People's Republic of China (MOST)[2017YFA0205200] ; Key Research Projects in Frontier Science of Chinese Academy of Sciences (CAS)[QYZDJ-SSW-JSC005]
项目资助者National Natural Science Foundation of China (NSFC) ; Ministry of Science and Technology of the People's Republic of China (MOST) ; Key Research Projects in Frontier Science of Chinese Academy of Sciences (CAS)
WOS研究方向Optics
WOS类目Optics
WOS记录号WOS:000450664900013
出版者OPTICAL SOC AMER
引用统计
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/22597
专题中国科学院分子影像重点实验室
通讯作者Wang, Kun
作者单位1.Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.Beijing Jiaotong Univ, Sch Comp & Informat Technol, Beijing 100044, Peoples R China
4.Beihang Univ, Beijing Adv Innovat Ctr Big Data Based Precis Med, Beijing 100191, Peoples R China
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GB/T 7714
Gao, Yuan,Wang, Kun,An, Yu,et al. Non model-based bioluminescence tomography using a machine-learning reconstruction strategy[J]. OPTICA,2018,5(11):1451-1454.
APA Gao, Yuan,Wang, Kun,An, Yu,Jiang, Shixin,Meng, Hui,&Tian, Jie.(2018).Non model-based bioluminescence tomography using a machine-learning reconstruction strategy.OPTICA,5(11),1451-1454.
MLA Gao, Yuan,et al."Non model-based bioluminescence tomography using a machine-learning reconstruction strategy".OPTICA 5.11(2018):1451-1454.
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