Abstract
Malaria is the leading cause of morbidity and mortality in tropical and subtropical countries. Conventional microscopy is the Gold standard in the diagnosis of the disease. However, it is prone to some shortcomings which include time consumption and difficultness in reproducing results. Alternative diagnosis techniques which yield superior results are quite expensive and hence inaccessible to developing countries where the disease is prevalent. Thus in this work, an accurate, speedy and affordable system of malaria detection using stained thin blood smear images was developed. The method uses Artificial Neural Network (ANN) to test for the presence of plasmodium parasites in thin blood smear images. Images of infected and non-infected erythrocytes were acquired, pre-processed, relevant features extracted from them and eventually diagnosis was made based on the features extracted from the images. Diagnosis entailed detection of plasmodium parasites. Classification accuracy of 95.0% in detection of infected erythrocyte was achieved with respect to results obtained by expert microscopists. The study revealed that artificial neural network (ANN) classifiers trained with colour features of infected stained thin blood smear images are suitable for detection. It was further shown that ANN classifiers can be trained to perform image segmentation.
Highlights
Malaria is a common but serious protozoan disease caused by peripheral blood, spleen or liver parasites of the genus Plasmodium
The study revealed that artificial neural network (ANN) classifiers trained with colour features of infected stained thin blood smear images are suitable for detection
Rapid Diagnostic Test (RDTs) which detects specific antigens derived from malaria parasites in lysed blood [5] and conventional microscopy [6,7] belong to the low cost class
Summary
Malaria is a common but serious protozoan disease caused by peripheral blood, spleen or liver parasites of the genus Plasmodium. Studies have shown that these techniques can yield high sensitivity and specificity to malaria diagnosis They are rarely used in developing countries where the disease is endemic because of the high cost, specialized infrastructure needs and handling difficulties. Rapid Diagnostic Test (RDTs) which detects specific antigens derived from malaria parasites in lysed blood [5] and conventional microscopy [6,7] belong to the low cost class. Commercially available RDT kits are specific to single species of plasmodium parasites and in cases where mixed infection is suspected, all the four kits should be used. The technique can be used to detect, and differentiate between different life stages and species of OPEN ACCESS
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