Development and implementation of an automated system to aid laboratory diagnosis using image processing
- 1 Department of Mechanical Engineering, University of Taubaté, Taubaté, Brasil
- 2 Department of Mechanical Engineering, University of Taubaté, Taubaté, Brasil
- 3 Department of Electrical Engineering, University of Taubaté, Taubaté, Brasil
- 4 Department of Electrical Engineering, University of Taubaté, Taubaté, Brasil
Abstract
The objective of this work is to provide an automatic system to count white blood cells in a blood smear. To do so an experiment was assembled, composed by a standard microscope with two step motors coupled to its knobs in order to move the microscope in x and y directions and a web cam which was mounted in the top of the microscope responsible for to acquire images from the smear. The step motors and the web cam are controlled by a microcomputer PC standard via software developed inDelphi. The motors use the parallel port to communicate with the PC and the camera use the USB port. The main idea is to set an initial point into the smear and the automated system will carry over the smear acquiring images (frames with 640 × 480 pixels) and counting the white blood cells encountered. The double histogram threshold technique is implemented to initially exclude the red cells from the image leaving only the white ones. Preliminaries results are obtained and show that the system is quite fast and has a good capacity of selection, even when different kinds of smear are used.
- Cseke, I. (1992) A fast segmentation scheme for white blood cell images. 11th IAPR International Conference on Pattern Recognition. Conference C: Image, Speech and Signal Analysis, The Hague, 30 Aug-3 Sep 1992, 530533.
- Theerapattanakul, J., Plodpai, J. and Pintavirooj, C. (2004) Na efficient method for segmentation step of automated white blood cell classifications. IEEE Region 10 Conference, 1, 191-194.
- Sinha, N. and Ramakrishnan, A.G. (2002) Blood cell segmentation using EM algorithm. Indian Conference on Computer Vision, Graphics and Image Processing.
- Koya, T.K. (2001) Sistema automático de contagem de células do sangue. Master Thesis, PPGEM-UFRGS, Porto Alegre.
- Schuch, N., et al. (2006) Sistema de aquisição de imagens para uso em microscopia óptica. Departamento de Engenharia Elétrica, UFRGS, Porto Alegre.
- Figueiro, T.R., Schuch, N., Cordeiro, V., Guimarães, L.V. and Susin, A.A. (2005) Automatic detection of blood cells on color images using image matching and flood map. XVIII Simpósio Brasileiro de Computação Gráfica e Processamento de Imagem, Workshop de Iniciação Científica.
- Lucarini, A.C., et al. (2003) Um sistema para a contagem semi-automática de microorganismos. Brazilian Symposium of Intelligent Automation, Bauru.
- Katz, A.R. (2000) Image analyses and supervisioned learning in the automated differentiation of white blood cells from microscopic images. Master Thesis, Department of Computer Science, RMIT.
- Zheng, Q., Milthorpe, B.K. and Jones, A.S. (2004) Direct neural network application for automated cell recognition. Cytometry Part A, 57, 1-9.
- Theera-Umpon, N. (2005) Patch-based white blood cell nucleus segmentation using fuzzy clustering. ECTI Transactions on Electrical Engineering, Electronics and Communications, 3, 2.
- Tripathi, S., Kumar, K., Singh, B.K. and Singh, R.P. (2012) Image segmentation: A review. International Journal of Computer Science and Management Research, 1, 838-843.