A fast forward 3D connection algorithm for mitochondria and synapse segmentations from serial EM images

doi:10.1186/s13040-018-0183-7

CORC > 自动化研究所 > 中国科学院自动化研究所 > 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, Weifu 1,2; Liu, Jing2 ; Xiao, Chi2 ; Deng, Hao 3; Xie, Qiwei 4,5; Han, Hua2,6,7
刊名	BIODATA MINING
	2018-11-05
卷号	11 页码:15
关键词	3D connection EM images Bwconncomp Mitochondria Synapse
ISSN号	1756-0381
DOI	10.1186/s13040-018-0183-7
通讯作者	Xie, Qiwei(qiwei.xie@bjut.edu.cn) ; Han, Hua(hua.han@ia.ac.cn)
英文摘要	BackgroundIt 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.
资助项目	National 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]
WOS关键词	ELECTRON-MICROSCOPY
WOS研究方向	Mathematical & Computational Biology
语种	英语
出版者	BMC
WOS记录号	WOS:000449264300001
资助机构	National 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
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/22779]
专题	类脑智能研究中心_神经计算及脑机交互
通讯作者	Xie, Qiwei; Han, Hua
作者单位	1.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
推荐引用方式 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.