Classification for avian malaria parasite Plasmodium gallinaceum blood stages by using deep convolutional neural networks.

ABSTRACT: The infection of an avian malaria parasite (Plasmodium gallinaceum) in domestic chickens presents a major threat to the poultry industry because it causes economic loss in both the quality and quantity of meat and egg production. Computer-aided diagnosis has been developed to automatically identify avian malaria infections and classify the blood infection stage development. In this study, four types of deep convolutional neural networks, namely Darknet, Darknet19, Darknet19-448 and Densenet201 are used to classify P. gallinaceum blood stages. We randomly collected a dataset of 12,761 single-cell images consisting of three parasite stages from ten-infected blood films stained by Giemsa. All images were confirmed by three well-trained examiners. The study mainly compared several image classi

SUBMITTER: Kittichai V 

PROVIDER: S-EPMC8376898 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature