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

fYear

2008

fDate

12-15 Oct. 2008

Firstpage

309

Lastpage

314

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/MESA.2008.4735751

Filename

4735751