Abstract
Malaria is most serious and widespread parasitic dieses of humans. Therefore, rapid and precise evaluation of parasitemia is necessary for malaria research. Manual test is the most widely used method for parasitemia evaluation but it is a time-consuming process and relies on the expertise of the techinician. This paper describes a algorithm for detecting and classifying malaria parasites in images Giemsa stained blood slides in order to evaluate the parasitemia of blood. A major point of this algorithm is an efficient method to segment cell images. So we introduce morphological and clamp splitting methods to cell images segmentation, that is, more accurate than classical segmentation algorithms.
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