Title: Application of machine vision for automated cell injection

Authors: Wenhui Wang, Darren Hewett, Christopher E. Hann, J. Geoffrey Chase, Xiao Qi Chen

Addresses: Department of Mechanical Engineering, University of Canterbury, Private Bag 4800, Christchurch 8140, New Zealand. ' Department of Mechanical Engineering, University of Canterbury, Private Bag 4800, Christchurch 8140, New Zealand. ' Department of Mechanical Engineering, University of Canterbury, Private Bag 4800, Christchurch 8140, New Zealand. ' Department of Mechanical Engineering, University of Canterbury, Private Bag 4800, Christchurch 8140, New Zealand. ' Department of Mechanical Engineering, University of Canterbury, Private Bag 4800, Christchurch 8140, New Zealand

Abstract: This paper presents image processing algorithms recognising cell structures for an automated cell injection system. For suspended zebrafish embryos, the convex hull and convexity defects of the cytoplasm contour are used. For adherent endothelial cells, the surface and shadow information of the nucleoli is used. Overall, 550 zebrafish embryos were 100% correctly recognised in online injection experiments. Compared to manual injection, the automated injection speed and reproducibility increase by up to 1.5-fold and 67% respectively. In the endothelial cell case, 436 nucleoli were 92% correctly recognised, paving the way for an automated adherent cell injection system to be developed.

Keywords: machine vision; image processing; cell injection; zebrafish embryos; endothelial cells; snake tracking; Delaunay triangulation; automated injection speed; automated injection reproducibility; cellular material delivery.

DOI: 10.1504/IJMMS.2009.024351

International Journal of Mechatronics and Manufacturing Systems, 2009 Vol.2 No.1/2, pp.120 - 134

Published online: 01 Apr 2009 *

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