CASIA OpenIR
A Method for Identification of Multisynaptic Boutons in Electron Microscopy Image Stack of Mouse Cortex
Deng, Hao1; Ma, Chao1; Han, Hua2; Xie, Qiwei2; Shen, Lijun1
Source PublicationAPPLIED SCIENCES-BASEL
2019-07-01
Volume9Issue:13Pages:19
Corresponding AuthorMa, Chao(chao.ma.must@gmail.com)
AbstractRecent electron microscopy (EM) imaging techniques make the automatic acquisition of a large number of serial sections from brain samples possible. On the other hand, it has been proven that the multisynaptic bouton (MSB), a structure that consists of one presynaptic bouton and multiple postsynaptic spines, is closely related to sensory deprivation, brain trauma, and learning. Nevertheless, it is still a challenging task to analyze this essential structure from EM images due to factors such as imaging artifacts and the presence of complicated subcellular structures. In this paper, we present an effective way to identify the MSBs on EM images. Using normalized images as training data, two convolutional neural networks (CNNs) are trained to obtain the segmentation of synapses and the probability map of the neuronal membrane, respectively. Then, a series of follow-up operations are employed to obtain rectified segmentation of synapses and segmentation of neurons. By incorporating this information, the MSBs can be reasonably identified. The dataset in this study is an image stack of mouse cortex that contains 178 serial images with a size of 6004 pixels x 5174 pixels and a voxel resolution of 2 nm x 2 nm x 50 nm. The precision and recall on MSB detection are 68.57% and 94.12%, respectively. Experimental results demonstrate that our method is conducive to biologists' research on MSBs' properties.
Keywordelectron microscopy multisynaptic bouton convolutional neural network image processing synapse neuron
DOI10.3390/app9132591
WOS KeywordACTIN-BASED PLASTICITY ; DENDRITIC SPINES ; SEGMENTATION ; SYNAPSES ; LTP
Indexed BySCI
Language英语
Funding ProjectScience and Technology Development Fund of Macau[0024/2018/A1] ; National Natural Science Foundation of China[61673381] ; Scientific Instrument Developing Project of the Chinese Academy of Sciences[YZ201671] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDB32030200] ; Special Program of the Beijing Municipal Science & Technology Commission[Z181100000118002]
Funding OrganizationScience and Technology Development Fund of Macau ; National Natural Science Foundation of China ; Scientific Instrument Developing Project of the Chinese Academy of Sciences ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Special Program of the Beijing Municipal Science & Technology Commission
WOS Research AreaChemistry ; Materials Science ; Physics
WOS SubjectChemistry, Multidisciplinary ; Materials Science, Multidisciplinary ; Physics, Applied
WOS IDWOS:000477031900012
PublisherMDPI
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/27761
Collection中国科学院自动化研究所
Corresponding AuthorMa, Chao
Affiliation1.Macau Univ Sci & Technol, Fac Informat Technol, Macau 999078, Peoples R China
2.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Deng, Hao,Ma, Chao,Han, Hua,et al. A Method for Identification of Multisynaptic Boutons in Electron Microscopy Image Stack of Mouse Cortex[J]. APPLIED SCIENCES-BASEL,2019,9(13):19.
APA Deng, Hao,Ma, Chao,Han, Hua,Xie, Qiwei,&Shen, Lijun.(2019).A Method for Identification of Multisynaptic Boutons in Electron Microscopy Image Stack of Mouse Cortex.APPLIED SCIENCES-BASEL,9(13),19.
MLA Deng, Hao,et al."A Method for Identification of Multisynaptic Boutons in Electron Microscopy Image Stack of Mouse Cortex".APPLIED SCIENCES-BASEL 9.13(2019):19.
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