Winarta, Tommy and Nugroho, Anto S. and Galinium, Maulahikmah (2017) Automated Status Classification Of Malaria Plasmodia From Thin Blood Smears Microphotograph Using Morphogeometrical Feature Extraction. Bachelor thesis, Swiss German University.

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Abstract

Malarial infection analyzed by manually examining a thin blood smear, done by an expert microscopist. Unfortunately, manual examination of the blood slide can be time consuming and is prone to human errors. Hence, this research aims to develop an algorithm that is based on the a priori knowledge of the experts so that the microscopic images can be analyzed with minimal human intervention. In this research, a morphogeometrical approach of feature extraction coupled with Naive Bayes classification theory are proposed to measure the infected cell’s size and shape to do species and life stage differentiation of P. falciparum, P. malariae, P. ovale, and P. vivax. This is done with the help of computational geometry, recursive bottleneck detection algorithm, and thresholding with Otsu’s method. In the end, the proposed algorithm when evaluated using real malaria cases produces a PPV (Positive Predictive Value) score of 77.14%, sensitivity score of 84.37%, and an

Item Type:	Thesis (Bachelor)
Uncontrolled Keywords:	Malaria; Thin Blood Smear; Computational Geometry; Naïve Bayes; Red Blood Cell Segmentation
Subjects:	Q Science > QA Mathematics > QA447 Geometry--Data processing R Medicine > RC Internal medicine > RC165 Tropical diseases
Divisions:	Faculty of Engineering and Information Technology > Department of Information Technology
Depositing User:	Astuti Kusumaningrum
Date Deposited:	12 May 2020 07:27
Last Modified:	12 May 2020 07:27
URI:	http://repository.sgu.ac.id/id/eprint/281

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