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
发表期刊Optica
2018-11
卷号5期号:11页码:1451-1454
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.

关键词Light Regularization Registration Information Algorithm Accuracy
DOI10.1364/OPTICA.5.001451
收录类别SCI
语种英语
引用统计
被引频次:54[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/173211/23540
专题中国科学院分子影像重点实验室
通讯作者Wang, Kun; Tian, Jie
作者单位1.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
第一作者单位中国科学院自动化研究所
通讯作者单位中国科学院自动化研究所
推荐引用方式
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.
条目包含的文件
文件名称/大小 文献类型 版本类型 开放类型 使用许可
manuscript.pdf(708KB)期刊论文作者接受稿开放获取CC BY-NC-SA浏览 下载
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Gao, Yuan]的文章
[Wang, Kun]的文章
[An, Yu]的文章
百度学术
百度学术中相似的文章
[Gao, Yuan]的文章
[Wang, Kun]的文章
[An, Yu]的文章
必应学术
必应学术中相似的文章
[Gao, Yuan]的文章
[Wang, Kun]的文章
[An, Yu]的文章
相关权益政策
暂无数据
收藏/分享
文件名: manuscript.pdf
格式: Adobe PDF
此文件暂不支持浏览
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。