Fast identification algorithms for manipulating biological cells
Date
2003-12-17
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
ORCID
Type
Degree Level
Masters
Abstract
The physical manipulation of biological cells is very attractive now in biotechnology (Butler, 1991)) because it opens the possibility of examining and manipulating single molecules. Other methods are based on chemical effects, electrical effects, etc., and they generally do not allow researchers to examine single molecules cell and, thus, to understand their interaction which may encode many useful pieces of information. Such physical manipulation is fully performed by robotic devices. In order to automate the process of physical manipulation, micro machine vision for the fast identification of the objects involved is required. Typical objects that are involved are cells, cell elements, holders and injectors. In the research described in this thesis, which was carried out in the Advanced Engineering Design Laboratory of the Mechanical Engineering Department, University of Saskatchewan, algorithms for the three objects (the cell, holder and injector) were developed, implemented and tested. The results obtained have shown that the fastest identification times for these three objects are respectively 0.12s for the cell oocyte, 6.78s/100 frames for the holder, and 6.72s/100 frames for the injector. These performances are acceptable in the context of the physical manipulation of biological cells. The goal of the research described in this thesis was to develop algorithms that would give a fast recognition of the cell manipulation system. With the aid of the algorithms, an automatic operation of the cell manipulation system would be achieved. Image process and pattern recognition techniques were used in developing the Visual C++® GUI algorithms that would automatically recognize the components of the cell manipulation system for the purpose of manipulating the cells.
Description
Keywords
Manipulation, Biological Cells, Algorithms
Citation
Degree
Master of Science (M.Sc.)
Department
Electrical Engineering
Program
Electrical Engineering