Automatic Reconstruction of Mitochondria and Endoplasmic Reticulum in Electron Microscopy Volumes by Deep Learning | |
Liu, Jing2,3; Li, Linlin3; Yang, Yang1; Hong, Bei2,3; Chen, Xi3; Xie, Qiwei3,5; Han, Hua2,3,4 | |
刊名 | FRONTIERS IN NEUROSCIENCE |
2020-07-21 | |
期号 | 14页码:13 |
关键词 | mitochondria endoplasmic reticulum electron microscopes segmentation 3D reconstruction |
DOI | 10.3389/fnins.2020.00599 |
英文摘要 | Together, mitochondria and the endoplasmic reticulum (ER) occupy more than 20% of a cell's volume, and morphological abnormality may lead to cellular function disorders. With the rapid development of large-scale electron microscopy (EM), manual contouring and three-dimensional (3D) reconstruction of these organelles has previously been accomplished in biological studies. However, manual segmentation of mitochondria and ER from EM images is time consuming and thus unable to meet the demands of large data analysis. Here, we propose an automated pipeline for mitochondrial and ER reconstruction, including the mitochondrial and ER contact sites (MAMs). We propose a novel recurrent neural network to detect and segment mitochondria and a fully residual convolutional network to reconstruct the ER. Based on the sparse distribution of synapses, we use mitochondrial context information to rectify the local misleading results and obtain 3D mitochondrial reconstructions. The experimental results demonstrate that the proposed method achieves state-of-the-art performance. |
资助项目 | National Natural Science Foundation of China[61673381] ; National Natural Science Foundation of China[31970960] ; Special Program of Beijing Municipal Science & Technology Commission[Z181100000118002] ; Strategic Priority Research Program of Chinese Academy of Science[XDB32030200] ; Bureau of International Cooperation, CAS[153D31KYSB20170059] ; Scientific Instrument Developing Project of Chinese Academy of Sciences[YZ201671] ; key program of the Ministry of Science and Technology of the People's Republic of China[2018YFC1005004] |
WOS关键词 | MITOFUSIN 2 ; DYNAMICS ; SEGMENTATION ; TRANSPORT ; SITES |
WOS研究方向 | Neurosciences & Neurology |
语种 | 英语 |
出版者 | FRONTIERS MEDIA SA |
WOS记录号 | WOS:000558860100001 |
资助机构 | National Natural Science Foundation of China ; Special Program of Beijing Municipal Science & Technology Commission ; Strategic Priority Research Program of Chinese Academy of Science ; Bureau of International Cooperation, CAS ; Scientific Instrument Developing Project of Chinese Academy of Sciences ; key program of the Ministry of Science and Technology of the People's Republic of China |
内容类型 | 期刊论文 |
源URL | [http://ir.ia.ac.cn/handle/173211/40439] |
专题 | 类脑智能研究中心_微观重建与智能分析 |
通讯作者 | Xie, Qiwei; Han, Hua |
作者单位 | 1.ShanghaiTech Univ, Sch Life Sci & Technol, Shanghai, Peoples R China 2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Sch Future Technol, Beijing, Peoples R China 3.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing, Peoples R China 4.CAS Ctr Excellence Brain Sci & Intelligence Techn, Shanghai, Peoples R China 5.Beijing Univ Technol, Data Min Lab, Beijing, Peoples R China |
推荐引用方式 GB/T 7714 | Liu, Jing,Li, Linlin,Yang, Yang,et al. Automatic Reconstruction of Mitochondria and Endoplasmic Reticulum in Electron Microscopy Volumes by Deep Learning[J]. FRONTIERS IN NEUROSCIENCE,2020(14):13. |
APA | Liu, Jing.,Li, Linlin.,Yang, Yang.,Hong, Bei.,Chen, Xi.,...&Han, Hua.(2020).Automatic Reconstruction of Mitochondria and Endoplasmic Reticulum in Electron Microscopy Volumes by Deep Learning.FRONTIERS IN NEUROSCIENCE(14),13. |
MLA | Liu, Jing,et al."Automatic Reconstruction of Mitochondria and Endoplasmic Reticulum in Electron Microscopy Volumes by Deep Learning".FRONTIERS IN NEUROSCIENCE .14(2020):13. |
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