Anggraini, Dian and Nugroho, Anto S. (2011) Automatic Status Identification of Microscopic Images Obtained from Malaria Thin Blood Smear. Bachelor thesis, Swiss German University.

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Abstract

Development of an accurate laboratory diagnostic tool, as recommended by WHO, is the key step to overcome the serious global health burden caused by malaria. This study aims to explore the possibility of computerized diagnosis of malaria and to develop a novel image processing algorithm to reliably detect the presence of malaria parasite from Plasmodium falciparum species in thin smears of Giemsa stained peripheral blood sample. The algorithm was designed as an expert system based on the method used by medical practitioner performing microscopy diagnosis of malaria. Digital images were acquired using a digital camera connected to a light microscope.Prior to processing, the images were subjected to gray-scale conversion to decrease color variability. Global thresholding was implemented to obtain erythrocyte and other blood cell components in each image. The segmented images were further processed to obtain informative features that were further used in classification stage. Two-stage classification using selected features was built based on Bayesian Decision Theory. Malaria samples, prepared and provided by Eijkman Institute of Molecular Biology Indonesia, were used to build and test the proposed algorithm.

Item Type:	Thesis (Bachelor)
Uncontrolled Keywords:	Malaria; Thin Blood Smears; Image Segmentation; Thresholding
Subjects:	R Medicine > R Medicine (General) > R856 Biomedical engineering R Medicine > R Medicine (General) > R858 Medical informatics R Medicine > RA Public aspects of medicine > RA644 Malaria, COVID-19
Divisions:	Faculty of Life Sciences and Technology > Department of Biomedical Engineering
Depositing User:	Astuti Kusumaningrum
Date Deposited:	04 Mar 2021 10:01
Last Modified:	04 Mar 2021 10:01
URI:	http://repository.sgu.ac.id/id/eprint/1047

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