Malaria remains a major burden on global health, with roughly 200 million cases worldwide
and more than 400,000 deaths per year. Besides biomedical research and political efforts …

Malaria, being an epidemic disease, demands its rapid and accurate diagnosis for proper
intervention. Microscopic image‐based characterization of erythrocytes plays an integral …

Visual quantification of parasitemia in thin blood films is a very tedious, subjective and time-
consuming task. This study presents an original method for quantification and classification …

Malaria is a serious disease responsible for thousands of deaths each year. Many efforts
have been made to aid in the diagnosis of malaria using machine learning techniques, but …

In this paper, we propose a comprehensive image characterization cum classification
framework for malaria‐infected stage detection using microscopic images of thin blood …

Malaria is a life-threatening disease causing by an infection of the protozoan parasite
Plasmodium. Plasmodium falciparum is the deadliest and most common human infected …

Aims Morphological recognition of red blood cells infected with malaria parasites is an
important task in the laboratory practice. Nowadays, there is a lack of specific automated …

Malaria, one of the deadliest diseases, is responsible for nearly 627,000 deaths every year.
It is diagnosed manually by pathologists using a microscope. It is time-consuming and …

This paper aims to develop the computer assisted malaria infected erythrocyte classification
based on a hybrid classifier. The major issues are feature extraction, optimal feature …

This research represents a method to detect malaria parasite in blood samples stained with
giemsa. In order to increase the accuracy of detecting, at the first step, the red blood cell …