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| Content Based Image Retrieval Approaches for
Detection of Malarial in Blood Images
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Full
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Source |
International Journal of Biometrics and Bioinformatics (IJBB) |
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Table of Contents |
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Volume: 5 Issue: 2 |
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Pages: 28-148 |
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Publication
Date: May / June 2011 |
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ISSN
(Online): 1985-2347 |
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Pages |
97 - 110 |
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Author(s) |
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Published
Date |
31-05-2011 |
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Publisher |
CSC
Journals, Kuala Lumpur,
Malaysia |
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ADDITIONAL
INFORMATION |
| Keywords Abstract References Cited by Related Articles Collaborative
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KEYWORDS: Falciparum, Vivax, Malariae, Giemsa |
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| Malaria is a serious global health problem, and rapid, accurate diagnosis is required to control the disease. An image
processing algorithm to automate the diagnosis of malaria in blood images is proposed in this paper. The image classification system is
designed to positively identify malaria parasites present in thin blood smears, and differentiate the species of malaria. Images are
acquired using a charge-coupled device camera connected to a light microscope. Morphological and novel threshold selection techniques
are used to identify erythrocytes (red blood cells) and possible parasites present on microscopic slides. Image features based on colour,
texture and the geometry of the cells and parasites are generated, as well as features that make use of a priori knowledge of the
classification problem and mimic features used by human technicians. A two-stage tree classifier using backpropogation feedforward
neural networks distinguishes between true and false positives, and then diagnoses the species (Plasmodium falciparum, P. vivax, P.
ovale or P. malariae) of the infection. Malaria samples obtained from the various biomedical research facilities are used for training and
testing of the system. Infected erythrocytes are positively identified with two measurable parameters namely sensitivity and a positive
predictive value (PPV), which makes the method highly sensitive at diagnosing a complete sample, provided many views are analyzed. |
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| Mohammad Imroze Khan : Colleagues
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| Bikesh Kumar Singh : Colleagues
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| Bibhudendra Acharya : Colleagues
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| Jigyasa Soni : Colleagues
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