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11-06-2017, 07:29 AM

Hi, could you please give me the code for detection and classification of malarial parasites

jaseela123d · 12-06-2017, 10:25 AM

Malaria is a serious disease for which the immediate diagnosis is required to control it. Microscopes are used to detect disease and pathologists use the manual method because there is a great possibility of false detection being made on the disease. If an erroneous detection is performed, the disease can become a more serious condition. Therefore, the study on computerized diagnosis is performed in this document, which will help in the immediate detection of the disease to some extent, so that appropriate treatment can be provided to the patient of malaria. Also used is the image processing algorithm that will reliably detect the presence of malaria parasite of Plasmodium falciparum species in fine smears of Giemsa-stained peripheral blood sample. Some imaging algorithms to automate the diagnosis of malaria in thin-blood smears are developed, but the percentage of parasitemia is often not as accurate as manual counting. One reason that results in this error is to ignore the cells at the edges of the images. This document eliminates human error by detecting the presence of malaria parasites in the blood sample through image processing and automation. This is achieved using Image Segmentation techniques to detect malaria parasites in images acquired from Giemsa-stained peripheral blood samples. This is a comparative study of two methods for the detection of malaria parasites, the first method is based on segmentation and the second uses feature extraction using minimum distance classifiers. We have built the malaria detection system in a robust way so that it is not affected by the exceptional conditions and reached high percentages of sensitivity, specificity, positive prediction and negative predictive values.

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