Authors :
Dr. Prabhanjan S; Swaroop S Kulkarni; Satvik R Kundargi; Ranjith Kumar R
Volume/Issue :
Volume 8 - 2023, Issue 5 - May
Google Scholar :
https://bit.ly/3TmGbDi
Scribd :
https://bit.ly/3MiT93g
DOI :
https://doi.org/10.5281/zenodo.7922711
Abstract :
Malaria is a fatal disease that leads to the
death of lakhs of individuals every year. Malaria is
caused by a microbe belonging to the Plasmodium
group. Five types of these organisms cause this disease
in a foreign body. P. falciparum, P. vivax, P. ovale,
and P. malariae are the five varieties of parasites that
cause malaria. P. Falciparum infected are the ones who
are more susceptible to keywords as others are mildly
infectious. Malaria is spread by a mosquito species
called anopheles it is the same that spreads dengue too.
However, this disease could be cured if detected at early
stages. Detecting malaria is an extremely challenging
aspect considering the morphological aspects of the
parasite. Malaria is more prevalent in tropical and subtropical climatic conditions. Owing to the parts of our
country the monsoon is the season where we could find
increased cases. Malarial parasites enter the human
body through mosquito saliva, which in turn is
transmitted to the blood. In the body of an organism, it
develops in the liver and matures there itself, and starts
to reproduce. Generally, malaria symptoms are seen
after 10-15 days the parasites intrude on the body. The
real challenging part is to check the growth of malaria
during the monsoon season in the rural part which faces
problems like a lack of doctors, nurses, equipment,
testing centers, and so on. The traditional methods of
detection are time-consuming and not so accurate.
Thus, our project aims to recognize and solve these
issues.
Keywords :
Image Processing, Convoluted Neural Network (CNN), Deep Learning, Machine Learning.
Malaria is a fatal disease that leads to the
death of lakhs of individuals every year. Malaria is
caused by a microbe belonging to the Plasmodium
group. Five types of these organisms cause this disease
in a foreign body. P. falciparum, P. vivax, P. ovale,
and P. malariae are the five varieties of parasites that
cause malaria. P. Falciparum infected are the ones who
are more susceptible to keywords as others are mildly
infectious. Malaria is spread by a mosquito species
called anopheles it is the same that spreads dengue too.
However, this disease could be cured if detected at early
stages. Detecting malaria is an extremely challenging
aspect considering the morphological aspects of the
parasite. Malaria is more prevalent in tropical and subtropical climatic conditions. Owing to the parts of our
country the monsoon is the season where we could find
increased cases. Malarial parasites enter the human
body through mosquito saliva, which in turn is
transmitted to the blood. In the body of an organism, it
develops in the liver and matures there itself, and starts
to reproduce. Generally, malaria symptoms are seen
after 10-15 days the parasites intrude on the body. The
real challenging part is to check the growth of malaria
during the monsoon season in the rural part which faces
problems like a lack of doctors, nurses, equipment,
testing centers, and so on. The traditional methods of
detection are time-consuming and not so accurate.
Thus, our project aims to recognize and solve these
issues.
Keywords :
Image Processing, Convoluted Neural Network (CNN), Deep Learning, Machine Learning.
