Journal
IEEE ROBOTICS AND AUTOMATION LETTERS
Volume 7, Issue 2, Pages 1395-1402Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LRA.2021.3140059
Keywords
Automation atmicro-nano scales; visual tracking; automated micromanipulation system; visual algorithms for micromanipulation; zebrafish heart micro-injection
Categories
Funding
- Inter-disciplinary Research Foundation of HIT
- National Natural Science Foundation of China [61933008, 61973099]
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This study presents an automated micro-injection method for zebrafish larva heart, including key technologies such as auto-focusing, injection pipette tracking, and heart detection. By optimizing strategies and algorithms, the efficiency and accuracy of injection are improved, with a success rate of 90%.
Micro-injection is one of the most efficient approaches to deliver foreign materials into zebrafish larva heart. Well-trained micro-injection technicians are required for such operation, and still the efficiency remains low and the work is laborious. As a result, automated micro-injection that is able to improve the efficiency and injection consistency is in great demand. Barriers like auto-focusing after changing of microscope magnification, accurate tracking of injection pipette, and zebrafish larva heart detection in three dimensions make the automation challenging. The proposed coarse-fine searching strategy and the depth of field optimized step lengths result in fast and accurate auto-focusing on the zebrafish and injection pipette. The injection pipette is tracked in real-time thanks to the proposed dynamical region of interest. Besides, the combination of y-Sobel filter and alpha-beta filter improves the noise resistance during pipette tracking, which helps to reduce the tracking error. With the proposed in-plane and out-of-plane heart detection algorithms, the zebrafish heart is detected in three dimensions efficiently and the accuracy is promising. The success rate for automated zebrafish larva heart micro-injection reached 90% with the proposed visual algorithms.
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