CASIA OpenIR  > 类脑智能研究中心  > 神经计算及脑机交互
A fast forward 3D connection algorithm for mitochondria and synapse segmentations from serial EM images
Li, Weifu1,2; Liu, Jing2; Xiao, Chi2; Deng, Hao3; Xie, Qiwei4,5; Han, Hua2,6,7
Source PublicationBIODATA MINING
ISSN1756-0381
2018-11-05
Volume11Pages:15
Corresponding AuthorXie, Qiwei(qiwei.xie@bjut.edu.cn) ; Han, Hua(hua.han@ia.ac.cn)
AbstractBackgroundIt is becoming increasingly clear that the quantification of mitochondria and synapses is of great significance to understand the function of biological nervous systems. Electron microscopy (EM), with the necessary resolution in three directions, is the only available imaging method to look closely into these issues. Therefore, estimating the number of mitochondria and synapses from the serial EM images is coming into prominence. Since previous studies have achieved preferable 2D segmentation performance, it holds great promise to obtain the 3D connection relationship from the 2D segmentation results.ResultsIn this paper, we improve upon Matlab's function bwconncomp and propose a fast forward 3D connection algorithm for mitochondria and synapse segmentations from serial EM images. To benchmark the performance of the proposed method, two EM datasets with the annotated ground truth are produced for mitochondria and synapses, respectively. Experimental results show that the proposed method can achieve the preferable connection performance that closely matches the ground truth. Moreover, it greatly reduces the computational burden and alleviates the memory requirements compared with the function bwconncomp.ConclusionsThe proposed method can be deemed as an effective strategy to obtain the 3D connection relationship from serial mitochondria and synapse segmentations. It is helpful to accurately and quickly quantify the statistics of the numbers, volumes, surface areas, and lengths, which will greatly facilitate the data analysis of neurobiology research.
Keyword3D connection EM images Bwconncomp Mitochondria Synapse
DOI10.1186/s13040-018-0183-7
WOS KeywordELECTRON-MICROSCOPY
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[61673381] ; National Natural Science Foundation of China[11771130] ; National Natural Science Foundation of China[61871177] ; National Natural Science Foundation of China[41501392] ; National Natural Science Foundation of China[61701497] ; Science and Technology Development Fund of Macau[044/2015/A2] ; Scientific Instrument Developing Project of Chinese Academy of Sciences[YZ201671] ; Bureau of International Cooperation, Chinese Academy of Sciences[153D31KYSB20170059] ; Special Program of Beijing Municipal Science & Technology Commission[Z161100000216146]
Funding OrganizationNational Natural Science Foundation of China ; Science and Technology Development Fund of Macau ; Scientific Instrument Developing Project of Chinese Academy of Sciences ; Bureau of International Cooperation, Chinese Academy of Sciences ; Special Program of Beijing Municipal Science & Technology Commission
WOS Research AreaMathematical & Computational Biology
WOS SubjectMathematical & Computational Biology
WOS IDWOS:000449264300001
PublisherBMC
Citation statistics
Cited Times:1[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/22780
Collection类脑智能研究中心_神经计算及脑机交互
Corresponding AuthorXie, Qiwei; Han, Hua
Affiliation1.Hubei Univ, Fac Math & Stat, 368 Youyi Rd, Wuhan 430062, Hubei, Peoples R China
2.Chinese Acad Sci, Inst Automat, 95 Zhongguancun East Rd, Beijing 100190, Peoples R China
3.Macau Univ Sci & Technol, Fac Informat Technol, Ave Wai Long, Taipa, Macau, Peoples R China
4.Beijing Univ Technol, Data Min Lab, 100 Ping Le Yuan, Beijing 100124, Peoples R China
5.Res Base Beijing Modern Mfg Dev, 100 Ping Le Yuan, Beijing 100124, Peoples R China
6.Chinese Acad Sci, Inst Biol Sci, Ctr Excellence Brain Sci & Intelligence Technol S, 320 Yue Yang Rd, Shanghai 200031, Peoples R China
7.Univ Chinese Acad Sci, Sch Future Technol, 19 Yuquan Rd, Beijing 100190, Peoples R China
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Corresponding Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Li, Weifu,Liu, Jing,Xiao, Chi,et al. A fast forward 3D connection algorithm for mitochondria and synapse segmentations from serial EM images[J]. BIODATA MINING,2018,11:15.
APA Li, Weifu,Liu, Jing,Xiao, Chi,Deng, Hao,Xie, Qiwei,&Han, Hua.(2018).A fast forward 3D connection algorithm for mitochondria and synapse segmentations from serial EM images.BIODATA MINING,11,15.
MLA Li, Weifu,et al."A fast forward 3D connection algorithm for mitochondria and synapse segmentations from serial EM images".BIODATA MINING 11(2018):15.
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