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Image Analysis System for Detection of Red Cell Disorders Using Artificial Neural Networks

Authors:

YM Hirimutugoda ,

Department of Computer Science and Engineering, Faculty of Engineering, University of Moratuwa, Moratuwa, Sri Lanka, LK
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Gamini Wijayarathna

Senior Lecturer, Department of Industrial Management, Faculty of Science, University of Kelaniya, Sri Lanka, LK
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Abstract

This paper investigates the possibility of rapid and accurate automated diagnosis of red blood cell disorders and describes a method to detect malarial parasites and thalassaemia in blood sample images acquired from light microscopes. As malaria and thalassaemia are life threatening diseases and an enormous global health problem, rapid and precise differentiation is necessary in clinical settings. The analysis of blood is a powerful diagnostic tool for the detection of these diseases. Visual inspection of microscopic images is the most widely used technique for determination of malaria and possible thalassaemia and it is a labour-intensive repetitive and time consuming task. Two back propagation Artificial Neural Network models (3 layers and 4 layers) was employed together with image analysis techniques to evaluate the accuracy of the classification in the recognition of medical image patterns associated with morphological features of erythrocytes in the blood. The three layers Artificial Neural Network (ANN) architecture had the best performance with an error of 2.74545e-005 and 86.54% correct recognition rate. The trained three layer ANN acts as a final detection classifier to determine diseases. A medical consultation system has been jointly used with this system to provide clinical decision making ability. A questioning and answering dialog on the basis of patient history, physical examination and routine diagnostic test has been conducted in the medical consultation system with image analyzing result made by the trained ANN.

Keywords: Malaria; Thalassaemia; Artificial Neural Network; Erythrocytes

DOI: 10.4038/sljbmi.v1i1.1484

Sri Lanka Journal of Bio-Medical Informatics 2009;1(1): 35-42

How to Cite: Hirimutugoda, Y. & Wijayarathna, G., (2010). Image Analysis System for Detection of Red Cell Disorders Using Artificial Neural Networks. Sri Lanka Journal of Bio-Medical Informatics. 1(1), pp.35–42. DOI: http://doi.org/10.4038/sljbmi.v1i1.1484
Published on 05 Jan 2010.
Peer Reviewed

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