Analysis of Microscopic Blood Samples for Detecting Malaria
Malaria is a mosquito-borne disease and it has been affecting millions of people worldwide since decades ago. The conventional method in diagnosing the blood disease is by using manual visual examination of microscopy blood smears. However, a computer-assisted system can be designed to assist in mal...
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ump-72602015-03-03T09:35:02Z http://umpir.ump.edu.my/id/eprint/7260/ Analysis of Microscopic Blood Samples for Detecting Malaria Saw Hui, Ann QA76 Computer software Malaria is a mosquito-borne disease and it has been affecting millions of people worldwide since decades ago. The conventional method in diagnosing the blood disease is by using manual visual examination of microscopy blood smears. However, a computer-assisted system can be designed to assist in malaria diagnosis by employing image processing, analysis and feature recognition algorithm. In terms of enhancing image for analysis, this study explores on a new approach by averaging results of two filters. In order to evaluate the performance of the proposed method, the image was further clustered by using K-Means, Expectation Maximization (EM) and Otsu’s threshold algorithm . 2013 Undergraduates Project Papers NonPeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/7260/1/CD7656.pdf Saw Hui, Ann (2013) Analysis of Microscopic Blood Samples for Detecting Malaria. Faculty of Computer Systems & Software Engineering, Universiti Malaysia Pahang. http://iportal.ump.edu.my/lib/item?id=chamo:77106&theme=UMP2 |
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Digital Repository |
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Local University |
institution |
Universiti Malaysia Pahang |
building |
UMP Institutional Repository |
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Online Access |
language |
English |
topic |
QA76 Computer software |
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QA76 Computer software Saw Hui, Ann Analysis of Microscopic Blood Samples for Detecting Malaria |
description |
Malaria is a mosquito-borne disease and it has been affecting millions of people worldwide since decades ago. The conventional method in diagnosing the blood disease is by using manual visual examination of microscopy blood smears. However, a computer-assisted system can be designed to assist in malaria diagnosis by employing image processing, analysis and feature recognition algorithm. In terms of enhancing image for analysis, this study explores on a new approach by averaging results of two filters. In order to evaluate the performance of the proposed method, the image was further clustered by using K-Means, Expectation Maximization (EM) and Otsu’s threshold algorithm . |
format |
Undergraduates Project Papers |
author |
Saw Hui, Ann |
author_facet |
Saw Hui, Ann |
author_sort |
Saw Hui, Ann |
title |
Analysis of Microscopic Blood Samples for Detecting Malaria |
title_short |
Analysis of Microscopic Blood Samples for Detecting Malaria |
title_full |
Analysis of Microscopic Blood Samples for Detecting Malaria |
title_fullStr |
Analysis of Microscopic Blood Samples for Detecting Malaria |
title_full_unstemmed |
Analysis of Microscopic Blood Samples for Detecting Malaria |
title_sort |
analysis of microscopic blood samples for detecting malaria |
publishDate |
2013 |
url |
http://umpir.ump.edu.my/id/eprint/7260/ http://umpir.ump.edu.my/id/eprint/7260/ http://umpir.ump.edu.my/id/eprint/7260/1/CD7656.pdf |
first_indexed |
2023-09-18T22:03:49Z |
last_indexed |
2023-09-18T22:03:49Z |
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1777414575014019072 |