Chromatin Detection in Malaria Thick Blood Film Using Automated Image Processing

Aeggarut Pinkaew; Tulaya Limpiti; Akraphon Trirat

doi:10.4028/www.scientific.net/AMM.781.616

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 781Chromatin Detection in Malaria Thick Blood Film...

Chromatin Detection in Malaria Thick Blood Film Using Automated Image Processing

Abstract:

Malaria is a serious global health problem and rapid, accurate diagnosis is required to control the disease. An image processing algorithm to aid the diagnosis of malaria on thick blood films is developed. Morphological and automatic threshold selection techniques are applied on two color components from the HSI color model to identify chromatins of P. Falciparum and P. Vivax malaria species on the images. Chromatins are positively identified with good sensitivities for both species. After identifying the position of chromatins, the algorithm splits the image into small sub-images, each with a chromatin in the center. These small images can subsequently be used by technician to classify malaria species more conveniently.

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Periodical:

Applied Mechanics and Materials (Volume 781)

Pages:

616-619

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.781.616

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Online since:

August 2015

Authors:

Aeggarut Pinkaew, Tulaya Limpiti*, Akraphon Trirat

Keywords:

Chromatin, Image Processing, Malaria, Thick Blood Film, Thresholding

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* - Corresponding Author

References

[1] Information on http: /www. who. int/malaria/media/world_malaria_report_2013/en.

Google Scholar

[2] S. Kareem, R.C. Morling and I. Kale, A novel method to count the red blood cells in thin blood films, 2011 IEEE Int. Symp. Circuits and Systems, (2011) 1021-1024.

DOI: 10.1109/iscas.2011.5937742

Google Scholar

[3] D. Anggraini, et. al., Automated status identification of microscopic images obtained from malaria thin blood smears using Bayes decision: A study case in Plasmodium Falciparum, 2011 Int. Conf. Advanced Computer Science and Information System (ICACSIS), (2011).

DOI: 10.1109/iceei.2011.6021762

Google Scholar

[4] M. Elter, H. Erik and Z. Thorsten, Detection of malaria parasites in thick blood films. 2011 Annual Int. Conf. Engineering in Medicine and Biology Society (EMBC), (2011) 5140-5144.

DOI: 10.1109/iembs.2011.6091273

Google Scholar

[5] R.C. Gonzalez, R.E. Woods, Digital Image Processing, 2 ed., Prentice Hall, New Jersey, (2002).

Google Scholar

[6] N. Otsu, A threshold selection method from gray-level histograms, IEEE Trans. Systems, man, and cybernetics SMC-9 (1979), 62-66.

DOI: 10.1109/tsmc.1979.4310076

Google Scholar