|Joint reconstruction of neuron and ultrastructure via connectivity consensus in electron microscope volumes|
|Hong,Bei1,2; Liu,Jing1,2; Zhai,Hao1,2; Liu,Jiazheng1,2; Shen,Lijun2; Chen,Xi2; Xie,Qiwei3; Han,Hua1,2,4|
|Source Publication||BMC Bioinformatics|
Background: Nanoscale connectomics, which aims to map the fine connections between neurons with synaptic-level detail, has attracted increasing attention in recent years. Currently, the automated reconstruction algorithms in electron microscope volumes are in great demand. Most existing reconstruction methodologies for cellular and subcellular structures are independent, and exploring the inter-relationships between structures will contribute to image analysis. The primary goal of this research is to construct a joint optimization framework to improve the accuracy and efficiency of neural structure reconstruction algorithms.
Results: In this investigation, we introduce the concept of connectivity consensus between cellular and subcellular structures based on biological domain knowledge for neural structure agglomeration problems. We propose a joint graph partitioning model for solving ultrastructural and neuronal connections to overcome the limitations of connectivity cues at different levels. The advantage of the optimization model is the simultaneous reconstruction of multiple structures in one optimization step. The experimental results on several public datasets demonstrate that the joint optimization model outperforms existing hierarchical agglomeration algorithms.
Conclusions: We present a joint optimization model by connectivity consensus to solve the neural structure agglomeration problem and demonstrate its superiority to existing methods. The intention of introducing connectivity consensus between different structures is to build a suitable optimization model that makes the reconstruction goals more consistent with biological plausible and domain knowledge. This idea can inspire other researchers to optimize existing reconstruction algorithms and other areas of biological data analysis.
|Keyword||Connectomics Reconstruction Connectivity concept Joint optimization Electron microscope volumes|
|WOS Keyword||IMAGE ; SYSTEM|
|Funding Project||National Science and Technology Innovation 2030 Major Program[2021ZD0204503] ; National Science and Technology Innovation 2030 Major Program[2021ZD0204500] ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; Strategic Priority Research Program of Chinese Academy of Sciences[XDB32030208] ; Strategic Priority Research Program of Chinese Academy of Sciences[XDA16021104] ; Program of Beijing Municipal Science & Technology Commission[Z201100008420004]|
|Funding Organization||National Science and Technology Innovation 2030 Major Program ; National Natural Science Foundation of China ; Strategic Priority Research Program of Chinese Academy of Sciences ; Program of Beijing Municipal Science & Technology Commission|
|WOS Research Area||Biochemistry & Molecular Biology ; Biotechnology & Applied Microbiology ; Mathematical & Computational Biology|
|WOS Subject||Biochemical Research Methods ; Biotechnology & Applied Microbiology ; Mathematical & Computational Biology|
|Sub direction classification||医学影像处理与分析|
|planning direction of the national heavy laboratory||其他|
|Corresponding Author||Shen,Lijun; Han,Hua|
|Affiliation||1.University of Chinese Academy of Sciences; School of Artificial Intelligence, School of Future Technology|
2.Chinese Academy of Sciences; National Laboratory of Pattern Recognition, Institute of Automation
3.Beijing University of Technology; Research Base of Beijing Modern Manufacturing Development
4.CAS Center for Excellence in Brain Science and Intelligence Technology
|First Author Affilication||Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China|
|Corresponding Author Affilication||Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China|
|Hong,Bei,Liu,Jing,Zhai,Hao,et al. Joint reconstruction of neuron and ultrastructure via connectivity consensus in electron microscope volumes[J]. BMC Bioinformatics,2022,23(1):23.|
|APA||Hong,Bei.,Liu,Jing.,Zhai,Hao.,Liu,Jiazheng.,Shen,Lijun.,...&Han,Hua.(2022).Joint reconstruction of neuron and ultrastructure via connectivity consensus in electron microscope volumes.BMC Bioinformatics,23(1),23.|
|MLA||Hong,Bei,et al."Joint reconstruction of neuron and ultrastructure via connectivity consensus in electron microscope volumes".BMC Bioinformatics 23.1(2022):23.|
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