Machine learning approach for automated screening of malaria parasite using light microscopic images

Article ID	Journal	Published Year	Pages	File Type
7986944	Micron	2013	10 Pages	PDF

Abstract

âº Staining variation has been removed from peripheral blood smear images. âº Impulse noise has been reduced. âº Erythrocytes are segmented using marker controlled watershed algorithm. âº Textural and morphological features have been extracted. âº Automated malaria infection (Plasmodium falciparum, Plasmodium vivax) stage recognition using pattern classification approach.

Keywords

Malaria parasite Texture Bayesian classifier Erythrocyte Machine learning

Related Topics

Physical Sciences and Engineering Materials Science Materials Science (General)

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Machine learning approach for automated screening of malaria parasite using light microscopic images

Authors

Dev Kumar Das, Madhumala Ghosh, Mallika Pal, Asok K. Maiti, Chandan Chakraborty,