Automated Diagnosis and Identification of Malarial Parasite in Blood Images

International Journal of Computer & Organization Trends  (IJCOT)          
© 2017 by IJCOT Journal
Volume - 7 Issue - 5
Year of Publication : 2017
AuthorsSwapna, Sreelatha Shenoy, Akhilraj .V .Gadagkar


Swapna, Sreelatha Shenoy, Akhilraj .V .Gadagkar "Automated Diagnosis and Identification of Malarial Parasite in Blood Images", International Journal of Computer & organization Trends (IJCOT), V7(5):24-28 Sep - Oct 2017, ISSN:2249-2593, Published by Seventh Sense Research Group.

AbstractMalaria is a mosquito borne infectious disease of humans and other animals caused by unicellular parasitic micro-organism of plasmodium genus under protozoa. This disease is transmitted through the bite from an infected female Anopheles mosquito. The organism is introduced from its saliva into the host circulatory system. Within the blood stream the parasite travels to the liver where they mature and reproduce. Malaria is a serious global health problem and nearly one million deaths is reported each year. Malaria causes symptoms that typically include high fever and headache that under severe infection can progress to coma or death. The disease is prevalent in tropical and subtropical regions around the equator region, including much of sub- Saharan Africa, Asia, and America. Accurate diagnosis is important to control the disease. There are several diagnostic tools available but microscopic analysis is the gold standard. An image processing method to automate the diagnosis of malaria in blood smear images is proposed in this paper using image segmentation approach for detection of malaria parasite.


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Malaria, Erythrocyte, Schizont, Plasmodium, Segmentation.