Publication:
An intelligent recognition procedure for trophozoite stages of plasmodium Knowlesi Malaria

cris.author.scopus-author-id 55987982900
cris.author.scopus-author-id 6603280096
cris.author.scopus-author-id 24345693200
cris.author.scopus-author-id 57202497341
cris.author.scopus-author-id 57214325384
cris.author.scopus-author-id 57546424200
cris.author.scopus-author-id 37108002800
cris.author.scopus-author-id 57218540740
dc.contributor.author Kanafiah S.N.A.M.
dc.contributor.author Mashor M.Y.
dc.contributor.author Mohamed Z.
dc.contributor.author Teh J.X.
dc.contributor.author Abdul Shukor S.A.
dc.contributor.author Zakaria N.Z.
dc.contributor.author Lim H.N.
dc.contributor.author Ali H.
dc.date.accessioned 2025-01-13T06:37:00Z
dc.date.available 2025-01-13T06:37:00Z
dc.date.issued 2018-01-01
dc.description.abstract Plasmodium (P.) Knowlesi is a fifth species of the malaria parasite in the world that caused a serious health problem. Current information suggests that P. Knowlesi is spread to people when an Anopheles mosquito infected by a monkey then bites and infects human (zoonotic transmission). Early identification of P. Knowlesi Malaria is an important step to an effective treatment. P. Knowlesi Malaria identification process is usually carried out with a 100x magnification of thin blood smear using microscope observation. However, this process is time-consuming and very tedious and strenuous for the human eyes. It also has a problem to differentiate between trophozoite, positive control (schizont and gametocyte) and negative control (white blood cell (WBC) and artefact). To overcome these situations, a computer-aided diagnosis system is developed to automatically identifying trophozoite stages of P. Knowlesi Malaria as early identification species, positive control and negative control. The processes involved starting from image acquisition, image processing and recognition. For image processing method, the most important part is the segmentation where the Otsu's method is utilised to obtain the region of interest (ROI) of the infected cell. The features consist of the size of infected cell and size of the object. Finally, the recognition method using Multilayer Perceptron (MLP) is applied. The results show that the proposed automatic procedure is capable of recognising the trophozoite stage of P. Knowlesi Malaria with an accuracy of 98.70% for training and 97.67% for testing, using MLP trained by Lavernberg Marquardt (LM).
dc.identifier.scopus 2-s2.0-85048543380
dc.identifier.uri https://hdl.handle.net/20.500.14170/11345
dc.relation.funding Kementerian Kesihatan Malaysia
dc.relation.grantno 9003-00586
dc.relation.ispartof Journal of Telecommunication, Electronic and Computer Engineering
dc.relation.ispartofseries Journal of Telecommunication, Electronic and Computer Engineering
dc.relation.issn 21801843
dc.subject Image Processing | MLP | P. Knowlesi Malaria | Recognition | Thin Blood Smears
dc.title An intelligent recognition procedure for trophozoite stages of plasmodium Knowlesi Malaria
dc.type Journal
dspace.entity.type Publication
oaire.citation.endPage 35
oaire.citation.issue 1-16
oaire.citation.startPage 31
oaire.citation.volume 10
oairecerif.affiliation.orgunit Universiti Malaysia Perlis
oairecerif.affiliation.orgunit Universiti Malaysia Perlis
oairecerif.affiliation.orgunit Universiti Sains Malaysia
oairecerif.affiliation.orgunit Universiti Malaysia Perlis
oairecerif.affiliation.orgunit Universiti Malaysia Perlis
oairecerif.affiliation.orgunit Universiti Sains Malaysia
oairecerif.affiliation.orgunit Universiti Malaysia Perlis
oairecerif.affiliation.orgunit Universiti Malaysia Perlis
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person.identifier.scopus-author-id 55987982900
person.identifier.scopus-author-id 6603280096
person.identifier.scopus-author-id 24345693200
person.identifier.scopus-author-id 57202497341
person.identifier.scopus-author-id 57214325384
person.identifier.scopus-author-id 57546424200
person.identifier.scopus-author-id 37108002800
person.identifier.scopus-author-id 57218540740
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