Title :
Machine Vision and Image Processing for Automated Cell Injection
Author :
Wang, W.H. ; Hewett, D. ; Hann, C.E. ; Chase, J.G. ; Chen, X.Q.
Author_Institution :
Dept. of Mech. Eng., Univ. of Canterbury, Christchurch
Abstract :
This paper presents image processing algorithms for cell structure recognition, which provides the desired deposition destinations without human interference for an automated cell injection system. Adherent cells (endothelial cells) are the main focus. The surface and shadow information of the nucleoli of endothelial cells is used to extract their locations, which subsequently produce a desired deposition destination inside the nucleus by Delaunay triangulation. 436 nucleoli were 92% correctly recognized, paving the way for an automated adherent cell injection system to be developed.
Keywords :
biology computing; cellular biophysics; computer vision; image processing; mesh generation; Delaunay triangulation; automated cell injection; cell structure recognition; endothelial cells; image processing; machine vision; nucleoli; Embryo; Focusing; Humans; Image processing; Image recognition; Machine vision; Microinjection; Morphology; Nanobioscience; Stem cells;
Conference_Titel :
Mechtronic and Embedded Systems and Applications, 2008. MESA 2008. IEEE/ASME International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-2367-5
Electronic_ISBN :
978-1-4244-2368-2
DOI :
10.1109/MESA.2008.4735751
