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Malaria Parasite Detection: Automated Method Using Microscope Color Image

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  • Anant R. Koppar

    (PES Research Center, India)

  • Venugopalachar Sridhar

    (P. E. S. College of Engineering, India)

Abstract

Healthcare Delivery Systems are becoming overloaded in developing countries like India and China. It is imperative that more efficient and cost effective processes are employed. One such requirement is the automatic detection of malaria parasites in stained blood smears. Malaria is a mosquito-borne infectious disease. Each year Malaria kills between one and three million people. The most conventional and gold standard test for the confirmation of the Malarial diagnosis is the peripheral blood smear examination. The paper investigates and develops an automated malaria diagnostic system based on the color image processing using Hue, Saturation & Intensity (HSI) model. The algorithm is designed to identify only parasites inside red blood cells (erythrocytes) to avoid false positive results. The work-flow process has enabled practical tele-pathology by allowing e-collaboration between lesser skilled technicians in rural areas and experts in urban areas, cutting down the total turnaround time for diagnosing malaria from days to minutes.

Suggested Citation

  • Anant R. Koppar & Venugopalachar Sridhar, 2011. "Malaria Parasite Detection: Automated Method Using Microscope Color Image," International Journal of E-Health and Medical Communications (IJEHMC), IGI Global, vol. 2(2), pages 68-81, April.
    • Handle: RePEc:igg:jehmc0:v:2:y:2011:i:2:p:68-81
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