Date

2022-2

Author

Ertürk, İzzet Fatih

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Cell counting is an important method used in many fields such as disease diagnosis in medicine. For example, the number of white blood cells in the blood gives information that there is a disease in the body. There are manual and automatic methods developed for cell counting. Although manual methods take a lot of time and are prone to error, they are preferred in many areas because they are less expensive than other methods. However, automated cell counting methods such as flow cytometry have been developed to achieve faster and more accurate results. The common feature of flow cytometry methods is that the fluid containing cells is passed through a microchannel one by one. These methods enable automatic cell counting as well as obtaining the physical properties of cells such as size. In cases where different cell types are examined together, cells can be classified by using the cell size and thus, the information about how many cells there are in each group can be obtained. For example, the type of disease can be determined by counting the types of white blood cells. The electrical impedance spectroscopy method, which is one of the flow cytometry methods, analyzes the effect of cell migration on the electric field applied to the microchannel, enabling the detection, counting and physical properties of cells. However, this method is quite expensive due to the devices that must be used for the method. In this thesis, it is aimed to develop an alternative method for counting the cells passed through the microchannel and classifying them according to their size. The flow of cells through the microchannel was recorded with a camera, and the images were processed with the proposed method, enabling the cells to be automatically detected, followed and counted, and classified according to their size. Image processing methods such as filtering, segmentation, opening and closing are used for automatic detection of cells, and Kalman filter and Hungarian assignment algorithm are used for tracking and counting. Classification according to their size was done with the K-medoids method and the ratio of different types of cells was found. The proposed method has been tested with various experiments and it has been concluded that cells can be detected correctly with image processing methods and cell counts can be successfully performed up to a certain flow rate.

Subject Keywords

Cell counting, Object tracking, Microchannel

URI

https://hdl.handle.net/11511/96246

Collections

Graduate School of Natural and Applied Sciences, Thesis