CLASSIFICATION OF MALARIA INFECTED ERYTHROCYTES USINGIMAGE PROCESSING
Jo Yee Chang · 2020
Malaria parasites are known to have caused deaths worldwide, especially in African regions where resources are limited. Currently, malaria diagnoses are still done manually by trained experts. Hence, the use of computer-aided detection systems for malaria detection or identification in erythrocytes is a valuable approach in reducing the need for human resources. This project aims to use image processing to extract the features of infected erythrocytes and study three commonly used machine learning techniques in order to compare their performance in classifying malaria infected erythrocytes.