CLASSIFICATION OF MALARIA INFECTED ERYTHROCYTES USING IMAGE PROCESSING
Malaria parasites are known to have caused deaths worldwide, especially in African regions where resources are limited. Currently, malaria diagnoses are still done manually by trained experts. Hence, the use of computer-aided detection systems for malaria detection or identification in erythrocytes...
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| Main Author: | |
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| Format: | Final Year Project Report |
| Language: | English English |
| Published: |
Universiti Malaysia Sarawak, (UNIMAS)
2020
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| Online Access: | http://ir.unimas.my/id/eprint/34024/1/Chang%20Jo%20Yee%20-%2024%20pgs.pdf http://ir.unimas.my/id/eprint/34024/4/Chang%20Jo%20Yee.pdf http://ir.unimas.my/id/eprint/34024/ |
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| Summary: | Malaria parasites are known to have caused deaths worldwide, especially in African regions where resources are limited. Currently, malaria diagnoses are still done manually by trained experts. Hence, the use of computer-aided detection systems for malaria detection or
identification in erythrocytes is a valuable approach in reducing the need for human resources. This project aims to use image processing to extract the features of infected erythrocytes and study three commonly used machine learning techniques in order to compare their performance in classifying malaria infected erythrocytes. |
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