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Microscopic malaria parasitemia diagnosis and grading on benchmark datasets.

08:00 EDT 12th September 2018 | BioPortfolio

Summary of "Microscopic malaria parasitemia diagnosis and grading on benchmark datasets."

Malaria parasitemia diagnosis and grading is hard and still far from perfection. Inaccurate diagnosis and grading has caused tremendous deaths rate particularly in young children worldwide. The current research deeply reviews automated malaria parasitemia diagnosis and grading in thin blood smear digital images through image analysis and computer vision based techniques. Actually, state-of-the-art reveals that current proposed practices present partially or morphology dependent solutions to the problem of computer vision based microscopy diagnosis of malaria parasitemia. Accordingly, a deep appraisal of the current practices is investigated, compared and analyzed on benchmark datasets. The open gaps are highlighted and the future directions are laid down for a complete automated microscopy diagnosis for malaria parasitemia based on those factors that have not been affected by other diseases. Moreover, a general computer vision framework to perform malaria parasitemia estimation/grading is constructed in universal directions. Finally, remaining problems are highlighted and possible directions are suggested.

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Name: Microscopy research and technique
ISSN: 1097-0029
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Malaria caused by PLASMODIUM VIVAX. This form of malaria is less severe than MALARIA, FALCIPARUM, but there is a higher probability for relapses to occur. Febrile paroxysms often occur every other day.

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