CASIA OpenIR  > 中国科学院分子影像重点实验室
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
Source PublicationOptica
2018-11
Volume5Issue:11Pages:1451-1454
Abstract

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.

KeywordLight Regularization Registration Information Algorithm Accuracy
DOI10.1364/OPTICA.5.001451
Indexed BySCI
Language英语
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Cited Times:3[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/23540
Collection中国科学院分子影像重点实验室
Corresponding AuthorWang, Kun; Tian, Jie
Affiliation1.CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
2.University of Chinese Academy of Sciences, Beijing 100049, China
3.School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China
4.Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beihang University, Beijing 100191, China
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Corresponding Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
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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