Segmentation of White Blood Cell Nucleus Using Active Contour

Authors

  • Nurhanis Izzati Che Marzuki Faculty of Bioscience and Medical Engineering, Universiti Teknologi Malaysia, 81310, UTM Johor Bahru, Johor, Malaysia
  • Nasrul Humaimi Mahmood Faculty of Electrical Engineering, Universiti Teknologi Malaysia, 81310, UTM Johor Bahru, Johor, Malaysia
  • Mohd Azhar Abdul Razak Faculty of Electrical Engineering, Universiti Teknologi Malaysia, 81310, UTM Johor Bahru, Johor, Malaysia

DOI:

https://doi.org/10.11113/jt.v74.4675

Keywords:

Image processing, white blood cell, active contour

Abstract

Image processing comes with various techniques. It uses a series of framework to transform an input image into an output image. In recent times, image processing technique has been extensively used in medical area. In order to overcome the problems of manual diagnosis in identifying the morphology of blood cells, the automated diagnosis is often used. Manual diagnosis required the observation of blood sample by expert hematologist and pathologist. This method may suffer from the presence of non-standard precision of human visual inspection. Due to this problem, this paper focused on semi-automated diagnosis that used image processing technique to perform the segmentation of the nucleus in white blood cell (WBC). Several image processing techniques are used including the active contour method. The results obtained are based on the parameter values obtained from segmentation process. The parameter value is calculated from the roundness equation. The value of 0.80 can be used to describe as a single leukocyte. 

References

J. Bain. 2004. A Beginner’s Guide to Blood Cells. Victoria: Blackwell Publishing.

L. Putzu, G. Caocci and C. D. Ruberto. 2014. Leucocytes Classification for Leukemia Detection using Image Processing Technique. Artificial Intelligence in Medicine. 62(3): 179–191.

J. M. Sharif, M. F. Miswan, M. A. Ngadi, M. S. Salam and M. Mahadi. 2012. Red Blood Cell Segmentation Using Masking and Watershed Algorithm : A Preliminary Study. International Conference on Biomedical Engineering. 27–28.

M. Mohamed and B. Far. 2012. An Enhanced Threshold Based Technique for White Blood Cells Nuclei Automatic Segmentation. IEEE 14th International Conference on e-Health Networking, Applications and Services. 202–207.

R. Dass and S. Devi. 2012. Image Segmentation Techniques. International Journal of Electronics & Communication Technology. 7109: 66–70.

T. F. Chan and L. A. Vese. 2001. Active Contours Without Edges. IEEE Transactions on Image Processing. 10(2): 266–77.

M. Kass, A. Witkin, and D. Terzopoulos. 1988. Snakes: Active Contour Models. International Journal of Computer Vision. 1: 321–331.

F. Sadeghian, Z. Seman, A. R. Ramli, B. H. Abdul Kahar and M. I. Saripan, 2009. A Framework for White Blood Cell Segmentation In Microscopic Blood Images Using Digital Image Processing. Biological Procedures Online. 11(1): 196–206.

N. H. Mahmood and M. A. Mansor. 2012. Red Blood Cells Estimation Using Hough Transform Technique. Signal & Image Processing : An International Journal (SIPIJ). 3(2): 53–64.

P. Guan and H. Yan. 2011. Blood Cell Image Segmentation Based on the Hough Transform and Fuzzy Curve Tracing. 2011 International Conference on Machine Learning and Cybernetics. 10–13.

H. Sun and Q. Zeng. 2011. Clustering-Based Touching-Cells Division. 2011 Eighth Web Information Systems and Applications Conference. 137–142.

L. Zou, J. Chen, J. Zhang and N. Garcia. 2010. Malaria Cell Counting Diagnosis within Large Field of View. 2010 International Conference on Digital Image Computing: Techniques and Applications. 172–177.

D. Anggraini, A. S. Nugroho, C. Pratama, I. E. Rozi, A. A. Iskandar and R. N. Hartono. 2011. Automated Status Identification of Microscopic Images Obtained from Malaria Thin Blood Smears. 2–7.

M. Mohamed, B. Far and A. Guaily. 2012. An Efficient Technique for White Blood Cells Nuclei Automatic Segmentation. IEEE International Conference on Systems, Man, and Cybernetics. 220–225.

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Published

2015-05-28

How to Cite

Segmentation of White Blood Cell Nucleus Using Active Contour. (2015). Jurnal Teknologi, 74(6). https://doi.org/10.11113/jt.v74.4675