09-03-2015, 02:09 PM
process of identification of malaria parasite and program details
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identification of malaria parasities using matlab
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process of identification of malaria parasite and program details
10-03-2017, 03:45 PM
With over 40% of the world's population at risk, 200-300 million infections each year, and an estimated 1.2 million deaths a year, malaria remains one of the most important public health problems of mankind from today. With the propensity of malaria parasites to rapidly develop resistance to newly developed therapies and recent failures of artemisinin-based drugs in Southeast Asia, there is an urgent need for novel antimalarial compounds with novel mechanisms of action against malaria Multi resistant. We present here a new algorithm for image analysis for the quantitative detection and classification of Plasmodium life cycles in the culture as well as the discrimination between viable and dead parasites in the samples treated with drugs. This new algorithm reliably estimates the number of red blood cells (isolated or clustered) per fluorescence imaging field, and accurately identifies erythrocytes parasitized based on spots of nuclei from parasites stained with high intensity DAPI and Mitotracker mitochondrial in Viable parasites. The performance of the algorithm was validated by manual counting of infected and uninfected red blood cells in multiple imaging fields, and quantitative analyzes of different stages of the parasite (early rings, rings, trophozoites, schizonts) Invasion of the chelators, in Closely synchronized cultures. In addition, the algorithm developed provided an effective parasitological concentration of 50 values (EC50) for both chloroquine and artemisinin, which were similar to the known EC50 growth inhibitor values for these compounds as determined using standard SYBR Green I assays And lactate dehydrogenase.
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