Open AccessAUTOMATED IMAGE PROCESSING FOR DIAGNOSING THE MALARIA SLIDES
Author(s) -
G. Abhishek,
P. Sushma,
J. NagaDivya,
K. Dhanunjaya Rao,
V. V. Sai Madhusudan
Publication year - 2022
Publication title -
international journal of research publication and reviews
Language(s) - English
Resource type - Journals
ISSN - 2582-7421
DOI - 10.55248/gengpi.2022.3.4.16
Subject(s) - malaria , plasmodium knowlesi , malarial parasites , convolutional neural network , parasite hosting , plasmodium (life cycle) , plasmodium falciparum , anopheles , artificial intelligence , blood film , virology , plasmodium vivax , computer science , biology , medicine , immunology , world wide web
Malaria is one of the most grievous health problems in the modern world, and it is caused by the bite of female Anopheles mosquitos. The parasite plasmodium erythrocytes are produced in the body. Malaria is caused by five Plasmodium parasites: P.falciparum, P.malariae, P.vivax, P.ovale, and P.knowlesi. In the traditional approach, blood samples are collected from the patient and then they were analyzed under a microscope further they will be sent for the manual testing procedure which consumes much time. To prevent this problem, we have proposed an efficient malaria diagnosing system which is developed using the help of a customized convolutional neural network (CNN), where we will pass the blood cells images and in return, automatically it evaluates the patient’s condition parasitized or uninfected.