A novel Cerenkov luminescence tomography approach using multilayer fully connected neural network
文献类型：期刊论文
| 作者 | Zhang,Zeyu1,2,3 ; Cai,Meishan1,3,4; Gao,Yuan1,3,4; Shi,Xiaojing3,4; Zhang,Xiaojun5; Hu,Zhenhua3,4,7; Tian,Jie2,3,4,6,7
|
| 刊名 | Physics in Medicine & Biology
 |
| 出版日期 | 2019-12-01 |
| 卷号 | 64期号:24 |
| ISSN号 | 0031-9155 |
| 关键词 | Cerenkov luminescence tomography (CLT) optical reconstruction photon propagation neural network inverse problem |
| DOI | 10.1088/1361-6560/ab5bb4 |
| 英文摘要 | Abstract Cerenkov luminescence tomography (CLT) has been proved as an effective tool for various biomedical applications. Because of the severe scattering of Cerenkov luminescence, the performance of CLT remains unsatisfied. This paper proposed a novel CLT reconstruction approach based on a multilayer fully connected neural network (MFCNN). Monte Carlo simulation data was employed to train the MFCNN, and the complex relationship between the surface signals and the true sources was effectively learned by the network. Both simulation and in vivo experiments were performed to validate the performance of MFCNN CLT, and it was further compared with the typical radiative transfer equation (RTE) based method. The experimental data showed the superiority of MFCNN CLT in terms of accuracy and stability. This promising approach for CLT is expected to improve the performance of optical tomography, and to promote the exploration of machine learning in biomedical applications. |
| 语种 | 英语 |
| 出版者 | IOP Publishing |
| WOS记录号 | IOP:0031-9155-64-24-AB5BB4 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/28620]  |
| 专题 | 自动化研究所_中国科学院分子影像重点实验室 |
| 作者单位 | 1.These authors contributed equally to this study. 2.Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi’an 710126, People’s Republic of China 3.CAS Key Laboratory of Molecular Imaging, Beijing Key Laboratory of Molecular Imaging, The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, People’s Republic of China 4.University of Chinese Academy of Sciences, Beijing 100049, People’s Republic of China 5.Department of Nuclear Medicine, Chinese PLA General Hospital, Beijing 100853, People’s Republic of China 6.Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beihang University, Beijing 100191, People’s Republic of China 7.Author to whom any correspondence should be addressed. |
| 推荐引用方式 GB/T 7714 | Zhang,Zeyu,Cai,Meishan,Gao,Yuan,et al. A novel Cerenkov luminescence tomography approach using multilayer fully connected neural network[J]. Physics in Medicine & Biology,2019,64(24). |
| APA | Zhang,Zeyu.,Cai,Meishan.,Gao,Yuan.,Shi,Xiaojing.,Zhang,Xiaojun.,...&Tian,Jie.(2019).A novel Cerenkov luminescence tomography approach using multilayer fully connected neural network.Physics in Medicine & Biology,64(24). |
| MLA | Zhang,Zeyu,et al."A novel Cerenkov luminescence tomography approach using multilayer fully connected neural network".Physics in Medicine & Biology 64.24(2019). |
入库方式： OAI收割
来源：自动化研究所
浏览0
下载0
收藏0
其他版本
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。