An automated cell detection algorithm for lensfree shadow imaging platform

Author

Roy, Matthieu ; Junhee Lee ; Geonsoo Jin ; Sungkyu Seo ; Myung-Hyun Nam

Author_Institution

Dept. of Electron. & Inf. Eng., Korea Univ., Sejong, South Korea

fYear

2013

fDate

10-11 Oct. 2013

Firstpage

1

Lastpage

3

Abstract

Here we propose an automated cell detection and counting algorithm for lens-free shadow imaging platform. This approach is based on the adaptive thresholding algorithm. The spatial variation of the threshold values is determined by the moving window technique. The shadow images of the Red Blood Cells(RBCs) are well detected and specified by the algorithm. The cell counting results from the algorithm for different concentration of blood cells are verified with the established cell counting results.

Keywords

biomedical optical imaging; blood; cellular biophysics; medical image processing; object detection; RBC; Red Blood Cells; adaptive thresholding algorithm; automated cell detection algorithm; blood cell concentration; cell counting; counting algorithm; lens-free shadow imaging platform; moving window technique; spatial variation; threshold value; Blood; Educational institutions; Histograms; Image processing; Imaging; Manuals; Signal processing algorithms; Adaptive threshold; Cytometry; Lens-free imaging;

fLanguage

English

Publisher

ieee

Conference_Titel

Emerging Trends in Communication, Control, Signal Processing & Computing Applications (C2SPCA), 2013 International Conference on

Conference_Location

Bangalore

Print_ISBN

978-1-4799-1082-3

Type

conf

DOI

10.1109/C2SPCA.2013.6749378

Filename

6749378