Deep learning-based computer assisted detection techniques for malaria parasite using blood smear images

Abstract

Malaria is a deadly infectious disease that affects humans.Malaria is caused by the parasite protozoan plasmodium, which may infiltrate erythrocytes and lead to a wide range of symptoms in humans.In accordance with World Health Organization (WHO), over 619, 000 people died from malaria in 2021, with an estimated 214 million people affected [1].Over 90% of these deaths happened in Africa, followed by over 6% in the South East Asia Region, Eastern Mediterranean, and 4% in the Western Pacific.In 2020 there were an expected 241 million cases of malaria and 627000 casualties caused by malaria.In 2019, there were 229 million confirmed cases of malaria and an estimated 409000 deaths.In 2018, 228 million malaria cases were detected, and causalities reached to 411000 [1]. *Author for correspondenceIn 2016, around 1.09 million and in 2017, approximately 0.84 million cases of malaria were documented in India, the majority of which were caused by the P. falciparum species [2].Dr. Ronald Ross first discovered malaria transmission in the human body by mosquitoes in 1897 [3].The main reason for malaria is a protozoan parasite.The plasmodium genus infects the red blood cells (RBC) of the human body, which causes malaria [4].Generally, female anopheles mosquitoes and human beings are the two main hosts infected by the parasite.When female Anopheles mosquitoes desire to foster their eggs, they bite and draw blood from the human body.If a parasite infects that person, then that same infected parasite blood is found in the mosquito, and that parasite reproduces and develops in the mosquito's body.When that infected mosquito bites another person, parasites containing the salivary gland are transferred into that person's blood [5].After transferring parasites into the human body by the mosquito, malaria parasites grow at a very high Research