Abstract
The automation methods and technologies of the single cell micro-injection reported in the literature have the common assumption that both the cell and the microtools has already been positioned within the microscopic field of view and well-focused. However, moving the microtools and biological cells from the macro field of view (macro-FOV) into the micro field of view (micro-FOV), and then further moving down into the culture medium and focusing were conducted manually and proved to be time consuming. In this work, we present algorithms and methods to automate this process. An electrothermal microgripper is used for picking and holding a zebrafish embryo instead of traditional micropipette. In order to position the microgripper into the micro-FOV, an extra macro camera is employed such that the microgripper jaws are under the macro-FOV. The micro-FOV is searched by moving the microgripper jaws in a serpentine path and zigzag path, respectively, and the grid-line identification algorithm is proposed to recognize the microgripper jaws that appear in the micro-FOV. Then, a contact detection algorithm is used to determine whether the gripper jaws are in the culture medium or not. Finally, eight algorisms are evaluated and compared to select the algorism with the best performance for auto-focusing the microgripper jaws in the culture medium. Up to 100 experiments are conducted to validate the proposed method for the macro-to-micro positioning and auto focusing of the microgripper jaws with the success rate 100% and 90%, respectively.
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This work was supported in part by 2018 Innovative Methodology Project (2018IM010400).
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Su, L., Zhang, H., Wei, H. et al. Macro-to-micro positioning and auto focusing for fully automated single cell microinjection. Microsyst Technol 27, 11–21 (2021). https://doi.org/10.1007/s00542-020-04891-w
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DOI: https://doi.org/10.1007/s00542-020-04891-w