A Method for Identification of Multisynaptic Boutons in Electron Microscopy Image Stack of Mouse Cortex
文献类型：期刊论文
| 作者 | Deng, Hao1; Ma, Chao1; Han, Hua2 ; Xie, Qiwei2; Shen, Lijun1
|
| 刊名 | APPLIED SCIENCES-BASEL
 |
| 出版日期 | 2019-07-01 |
| 卷号 | 9期号:13页码:19 |
| 关键词 | electron microscopy multisynaptic bouton convolutional neural network image processing synapse neuron |
| DOI | 10.3390/app9132591 |
| 通讯作者 | Ma, Chao(chao.ma.must@gmail.com) |
| 英文摘要 | Recent 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. |
| WOS关键词 | ACTIN-BASED PLASTICITY ; DENDRITIC SPINES ; SEGMENTATION ; SYNAPSES ; LTP |
| 资助项目 | Science 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] |
| WOS研究方向 | Chemistry ; Materials Science ; Physics |
| 语种 | 英语 |
| WOS记录号 | WOS:000477031900012 |
| 出版者 | MDPI |
| 资助机构 | Science 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 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/27760]  |
| 专题 | 类脑智能研究中心_微观重建与智能分析 |
| 通讯作者 | Ma, Chao |
| 作者单位 | 1.Macau Univ Sci & Technol, Fac Informat Technol, Macau 999078, Peoples R China 2.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China |
| 推荐引用方式 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. |
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。