Automated Silicon-Substrate Ultra-Microtome for Automating the Collection of Brain Sections in Array Tomography
文献类型:期刊论文
作者 | Cheng, Long1,2![]() ![]() ![]() ![]() ![]() |
刊名 | IEEE-CAA JOURNAL OF AUTOMATICA SINICA
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出版日期 | 2021-02-01 |
卷号 | 8期号:2页码:389-401 |
关键词 | Array tomography automatic collection system brain sections microscopic object detection serial section |
ISSN号 | 2329-9266 |
DOI | 10.1109/JAS.2021.1003829 |
英文摘要 | Understanding the structure and working principle of brain neural networks requires three-dimensional reconstruction of brain tissue samples using array tomography method. In order to improve the reconstruction performance, the sequence of brain sections should be collected with silicon wafers for subsequent electron microscopic imaging. However, the current collection of brain sections based on silicon substrate involve mainly manual collection, which requires the involvement of automation techniques to increase collection efficiency. This paper presents the design of an automatic collection device for brain sections. First, a novel mechanism based on circular silicon substrates is proposed for collection of brain sections; second, an automatic collection system based on microscopic object detection and feedback control strategy is proposed. Experimental results verify the function of the proposed collection device. Three objects (brain section, left baffle, right baffle) can be detected from microscopic images by the proposed detection method. Collection efficiency can be further improved with position feedback of brain sections well. It has been experimentally verified that the proposed device can well fulfill the task of automatic collection of brain sections. With the help of the proposed automatic collection device, human operators can be partially liberated from the tedious manual collection process and collection efficiency can be improved. |
资助项目 | National Natural Science Foundation of China[61873268] ; National Natural Science Foundation of China[62025307] ; National Natural Science Foundation of China[U1913209] ; Beijing Natural Science Foundation[JQ19020] |
WOS研究方向 | Automation & Control Systems |
语种 | 英语 |
WOS记录号 | WOS:000607401900007 |
出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
资助机构 | National Natural Science Foundation of China ; Beijing Natural Science Foundation |
源URL | [http://ir.ia.ac.cn/handle/173211/42867] ![]() |
专题 | 自动化研究所_复杂系统管理与控制国家重点实验室_先进机器人控制团队 复杂系统管理与控制国家重点实验室_水下机器人 |
通讯作者 | Cheng, Long |
作者单位 | 1.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 2.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China |
推荐引用方式 GB/T 7714 | Cheng, Long,Liu, Weizhou,Zhou, Chao,et al. Automated Silicon-Substrate Ultra-Microtome for Automating the Collection of Brain Sections in Array Tomography[J]. IEEE-CAA JOURNAL OF AUTOMATICA SINICA,2021,8(2):389-401. |
APA | Cheng, Long,Liu, Weizhou,Zhou, Chao,Zou, Yongxiang,&Hou, Zeng-Guang.(2021).Automated Silicon-Substrate Ultra-Microtome for Automating the Collection of Brain Sections in Array Tomography.IEEE-CAA JOURNAL OF AUTOMATICA SINICA,8(2),389-401. |
MLA | Cheng, Long,et al."Automated Silicon-Substrate Ultra-Microtome for Automating the Collection of Brain Sections in Array Tomography".IEEE-CAA JOURNAL OF AUTOMATICA SINICA 8.2(2021):389-401. |
入库方式: OAI收割
来源:自动化研究所
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