Chandra, Raymond Septevan and Nugroho, Anto S. and Galinium, Maulahikmah (2015) Automated Classification of Malaria Plasmodia from Thin Blood Smears Microphotograph. Bachelor thesis, Swiss German University.

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Abstract

One of the deadly diseases that can be found in a tropical or sub-tropical climate country like Indonesia is Malaria. Malaria is not a new trending topic for a disease category nowadays. Automated malaria detection by using host blood samples is needed to improve time efficiency for diagnosing as the first step for treatment. With this work, automated detection is built using a thin blood smears microphotograph that is stained using a Giemsa stain as input material. Image processing algorithms are constructed with image pre-processing, image thresholding, blood cell segmentation, suspected erythrocyte classification and plasmodium classification. Two stages of classification are used in plasmodium classification by observing the size of object and the intensity supported by the Bayes classifier. The output from this program is expected to tell what kind of human plasmodium (Plasmodium falciparum, Plasmodium malariae, Plasmodium vivax and Plasmodium ovale) has infected the host.

Item Type:	Thesis (Bachelor)
Uncontrolled Keywords:	Malaria; Thin Blood Smears; Malaria Classification; Plasmodium Classification; Image Pre-processing; Bayes Classifier; Otsu Thresholding.
Subjects:	R Medicine > RC Internal medicine > RC165 Tropical diseases T Technology > T Technology (General) > T58.5 Information technology
Divisions:	Faculty of Engineering and Information Technology > Department of Information Technology
Depositing User:	Atroridho Rizky
Date Deposited:	04 Nov 2020 14:45
Last Modified:	04 Nov 2020 14:45
URI:	http://repository.sgu.ac.id/id/eprint/1725

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