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Reseach Article

A Novel Method for Automatic Detection of Malaria Parasite Stage in Microscopic Blood Image

by Kshipra Charpe, V.K. Bairagi, Shama Desarda, Sheetal Barshikar
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 128 - Number 17
Year of Publication: 2015
Authors: Kshipra Charpe, V.K. Bairagi, Shama Desarda, Sheetal Barshikar
10.5120/ijca2015906763

Kshipra Charpe, V.K. Bairagi, Shama Desarda, Sheetal Barshikar . A Novel Method for Automatic Detection of Malaria Parasite Stage in Microscopic Blood Image. International Journal of Computer Applications. 128, 17 ( October 2015), 32-37. DOI=10.5120/ijca2015906763

@article{ 10.5120/ijca2015906763,
author = { Kshipra Charpe, V.K. Bairagi, Shama Desarda, Sheetal Barshikar },
title = { A Novel Method for Automatic Detection of Malaria Parasite Stage in Microscopic Blood Image },
journal = { International Journal of Computer Applications },
issue_date = { October 2015 },
volume = { 128 },
number = { 17 },
month = { October },
year = { 2015 },
issn = { 0975-8887 },
pages = { 32-37 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume128/number17/22968-2015906763/ },
doi = { 10.5120/ijca2015906763 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:21:59.571235+05:30
%A Kshipra Charpe
%A V.K. Bairagi
%A Shama Desarda
%A Sheetal Barshikar
%T A Novel Method for Automatic Detection of Malaria Parasite Stage in Microscopic Blood Image
%J International Journal of Computer Applications
%@ 0975-8887
%V 128
%N 17
%P 32-37
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Malaria is caused due to the mosquito bite hence the parasite enter into blood through the saliva of the mosquito. The malaria parasite directly infects the red blood cells, therefore to design an automatic detection system, the red blood cells should be segmented from the artifacts and background in a microscopic image. Here in this paper watershed transform is used with the distance transform which separates even the overlapped red blood cells more efficiently, which are useful for the diagnosis of parasite and for the parasitemia too. The result shows improvement in diagnostic accuracy of detection of the parasite in Red Blood Cells and also describing the life cycle stage of the parasite. The accuracy, sensitivity and specificity achieved were as 97.7%, 97.4% and 97.7% respectively.

References
  1. World Health Organization (WHO) statistical analysis of Malaria diseases in the year 2013. http://www.who.int/malaria/publications/world_malaria_report_2013/en/
  2. http://www.nvbdcp.gov.in/malaria9.html (National Vector Borne Disease Control Program (NVDCP) Directorate General of Health Services Ministry of Health and Family Welfare, Delhi)
  3. World Health Organization. Basic malaria microscopy, 2nd edition, WHO Press, pp-7-88, 2010.
  4. Centres for Disease Control and Prevention: Public Health Image Library [online]. 2005 www: http://phil.cdc.gov/phil/ home.asp.
  5. Priyamvada Jain, Babina Chakma, Sanjukta Patra, and Pranab Goswami, “Potential Biomarkers and Their Applications for Rapid and Reliable Detection of Malaria”, Hindawi Publishing Corporation BioMed Research International Volume 2014, Article ID 852645, pp1-20, 2014.
  6. Yashasvi Purwar, Sirish L Shah, Gwen Clarke, Areej Almugairi and Atis Muehlenbachs, “Automated and unsupervised detection of malaria parasites in microscopic images”, Springer-Malaria Journal, Vol. 10, pp 11-22, 2011.
  7. K. M. Khatria, V. R. Ratnaparkheb, S. S. Agrawal, A. S. Bhalchandrac, “Image Processing Approach for Malaria Parasite Identification”, International Journal of Computer Applications,National Conference on Growth of Technologies in Electronics, Telecom and Computers - India's Perception, 2013.
  8. Subhamoy Mandal, J Chatterjee, “Segmentation of Blood Smear Images using Normalized Cuts for Detection of Malarial Parasites”, 2010 Annual IEEE India Conference (INDICON), pp1-4, 2010.
  9. Aimi Salihah, Abdul-Nasir, Mohd Yusoff Mashor, Zeehaida Mohamed, “Colour Image Segmentation Approach for Detection of Malaria Parasites Using Various Colour Models and k-Means Clustering”, Wseas Transactions on Biology and Biomedicine, Vol. 10, Issue 1, pp 41-55, January 2013.
  10. Yazan M. Alomari, Siti Norul Huda Sheikh Abdullah, Raja Zaharatul Azma and Khairuddin Omar, “Automatic Detection and Quantification of WBCs and RBCs Using Iterative Structured Circle Detection Algorithm”, Hindawi Publishing Corporation Computational and Mathematical Methods in Medicine Volume of 2014, Article ID 979302, pp1-17, 2014.
  11. V. V. Panchbhai, L. B. Damahe, A. V. Nagpure, and P. N. Chopkar, “RBCs and parasites segmentation from thin smear blood cell images”, I.J. Image, Graphics and Signal Processing, Vol.10, pp 54-60, 2012.
  12. A.S.Abdul Nasir, M.Y.Mashor and Z.Mohamed “Segmentation Based Approach for Detection of Malaria Parasites Using Moving K-Means Clustering”, IEEE EMBS International Conference on Biomedical Engineering and Science, pp 653-658, Dec 2012.
  13. S.Kareem, R. C. S. Morling, “Automated P.falciparium detection system for Post-treatment Malaria Diagnosis using Modified Annular Ring Ratio Method”, 14th International conference on modelling and simulation, IEEE computer society, pp 432-436 2014.
  14. S.Kareem, R. C. S. Morling, “Automated Malaria Parasite Detection in Thin Blood Films, A Hybrid Illumination and color constancy Insensitive, Morphological Approach”, 14th International conference on modelling and simulation, IEEE computer society, pp-240-243, 2012.
  15. Iis Hamsir Ayub Wahab, Adhi Susanto, P. Insap Santosa, Maesadji TJokronegoro, “Principal Component analysis combined with second order statistical feature method for malaria parasite classification ”, Journal of Theoretical and Applied Information Technology, Vol 63, Issue 1, May 2014.
  16. S.S.Savkare, S.P.Narote, “Automatic System for Classification of Erythrocytes Infected with Malria and Identification of Parasite life Stage”, 2nd International Conference on Communication, Computing & Security [ICCCS-2012] Elsevier, Vol 6, pp 405-410, 2012.
  17. Cloppet F, Boucher A, “Segmentation of overlapping/aggregating nuclei cells in biological images”, Pattern Recognition, 2008. ICPR 2008 19th International IEEE Conference, pp 1-4, 2008.
  18. Kshipra Charpe, Dr. V. K. Bairagi, “Automated Malaria Parasite and there stage Detection in Microscopic Blood Images”, 9th IEEE Sponsored International Conference on Intelligent Systems & Control, 9th – 10th January, 2015.
  19. Dr. Arora, “Mediacal Parasitology”, Second edition, CBS publisher and distributors, chapter 5-sporozoa , malaria parasite, pp 67-80.
  20. Rafael C. Gonzalez and Richard E. Woods, “Digital Image Processing”, Third edition 2009.
Index Terms

Computer Science
Information Sciences

Keywords

Watershed Parasitemia Texture and Statistic Features.