Automatic Reconstruction of Mitochondria and Endoplasmic Reticulum in Electron Microscopy Volumes by Deep Learning

doi:10.3389/fnins.2020.00599

	Automatic Reconstruction of Mitochondria and Endoplasmic Reticulum in Electron Microscopy Volumes by Deep Learning
	Liu, Jing 1,2; Li, Linlin 1; Yang, Yang3 ; Hong, Bei 1,2; Chen, Xi 1; Xie, Qiwei 1,4; Han, Hua 1,2,5
	2020-07-21
发表期刊	FRONTIERS IN NEUROSCIENCE (IF:3.2[JCR-2023],4.3[5-Year])
EISSN	1662-453X
卷号	14
发表状态	已发表
DOI	10.3389/fnins.2020.00599
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.
关键词	mitochondria endoplasmic reticulum electron microscopes segmentation 3D reconstruction
URL	查看原文
收录类别	SCI ; SCIE
语种	英语
资助项目	National Natural Science Foundation of China[61673381][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研究方向	Neurosciences & Neurology
WOS类目	Neurosciences
WOS记录号	WOS:000558860100001
出版者	FRONTIERS MEDIA SA
WOS关键词	MITOFUSIN 2 ; DYNAMICS ; SEGMENTATION ; TRANSPORT ; SITES
原始文献类型	Article
引用统计	正在获取...
文献类型	期刊论文
条目标识符	https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/122944
专题	生命科学与技术学院_PI研究组_杨扬组
通讯作者	Xie, Qiwei; Han, Hua
作者单位	1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing, Peoples R China 2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Sch Future Technol, Beijing, Peoples R China 3.ShanghaiTech Univ, Sch Life Sci & Technol, Shanghai, Peoples R China 4.Beijing Univ Technol, Data Min Lab, Beijing, Peoples R China 5.CAS Ctr Excellence Brain Sci & Intelligence Techn, Shanghai, 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.
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.
MLA	Liu, Jing,et al."Automatic Reconstruction of Mitochondria and Endoplasmic Reticulum in Electron Microscopy Volumes by Deep Learning".FRONTIERS IN NEUROSCIENCE 14(2020).