期刊
IEEE ROBOTICS AND AUTOMATION LETTERS
卷 5, 期 2, 页码 1167-1174出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LRA.2020.2965870
关键词
Biological cell manipulation; computer vision for other robotic applications; object detection; segmentation and categorization
类别
资金
- Research Grants Council of Hong Kong SAR, China [11209917, T42-409/18-R]
Automated microinjection systems for suspension cells have been studied for years. Nevertheless, microinjection systems for adherent cells still suffer from laborious manual operations and low productivity. This paper presents a new automated microinjection system with high productivity for adherent cells. This system enhances productivity through four approaches. First, cells are detected automatically to replace manual selections. Second, the injection paths of detected cells are optimized rapidly to save time. Third, the penetration depth is adjusted adaptively according to the moving plane of the dish holder plate. Finally, constant outflow-based injection is adopted to minimize clogging. The first three approaches aim to improve the injection speed, and the last one aims to extend the usage time of micropipettes. Experiments of massive injections on MC3T3-E1 cells are performed to evaluate cell detection efficiency, injection speed, success rate, and survival rate. Results confirm that the system allows injections of over 1500 cells in one hour without much training and preparation a priori.
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