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作者:

Xie, Qiwei (Xie, Qiwei.) (学者:谢启伟) | Chen, Xi (Chen, Xi.) | Shen, Lijun (Shen, Lijun.) | Li, Guoqing (Li, Guoqing.) | Ma, Hongtu (Ma, Hongtu.) | Han, Hua (Han, Hua.)

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EI Scopus CSCD CSSCI

摘要:

This paper aims to solve the problem of high throughput automated data analysis of brain microstructure reconstruction by using the solution of systems engineering that consists of hardware, software and algorithm. To solve the key issues of limit analysis efficiency such as registration of large-volume distorted image, dense neural structure recognition, ambiguous neural connections and multi-source data fusion etc, classification method in accordance with the biological characteristics of neural structure is proposed by the realization of the samples preparation, automatic cutting, microscopic imaging, 3D reconstruction and software platform building etc. Furthermore, it provides a theoretical basis and solution for building engineering platform for large volume neural structure reconstruction and meets the brain science research of high-throughput neural circuit network reconstruction demand. © 2017, Editorial Board of Journal of Systems Engineering Society of China. All right reserved.

关键词:

Image reconstruction Brain Deep learning Learning systems Data fusion

作者机构:

  • [ 1 ] [Xie, Qiwei]School of Economics and Management, Beijing University of Technology, Beijing; 100124, China
  • [ 2 ] [Xie, Qiwei]Institute of Automation, Chinese Academy of Sciences, Beijing; 100190, China
  • [ 3 ] [Chen, Xi]Institute of Automation, Chinese Academy of Sciences, Beijing; 100190, China
  • [ 4 ] [Shen, Lijun]Institute of Automation, Chinese Academy of Sciences, Beijing; 100190, China
  • [ 5 ] [Li, Guoqing]Institute of Automation, Chinese Academy of Sciences, Beijing; 100190, China
  • [ 6 ] [Ma, Hongtu]Institute of Automation, Chinese Academy of Sciences, Beijing; 100190, China
  • [ 7 ] [Han, Hua]Institute of Automation, Chinese Academy of Sciences, Beijing; 100190, China
  • [ 8 ] [Han, Hua]Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai; 200031, China
  • [ 9 ] [Han, Hua]Future Technical College, University of Chinese Academy of Sciences, Beijing; 101407, China

通讯作者信息:

  • [han, hua]institute of automation, chinese academy of sciences, beijing; 100190, china;;[han, hua]center for excellence in brain science and intelligence technology, chinese academy of sciences, shanghai; 200031, china;;[han, hua]future technical college, university of chinese academy of sciences, beijing; 101407, china

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来源 :

System Engineering Theory and Practice

ISSN: 1000-6788

年份: 2017

期: 11

卷: 37

页码: 3006-3017

被引次数:

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SCOPUS被引频次: 8

ESI高被引论文在榜: 0 展开所有

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