Publication:
Modelling of Retinal Images for Analysis of Diabetic Retinopathy Severity Levels

cris.author.scopus-author-id 57391849700
cris.author.scopus-author-id 26653958200
cris.author.scopus-author-id 22137274300
cris.author.scopus-author-id 57212344599
cris.author.scopus-author-id 57215715847
cris.author.scopus-author-id 57201525827
cris.virtual.department Universiti Malaysia Perlis
cris.virtual.department Universiti Malaysia Perlis
cris.virtual.department Universiti Malaysia Perlis
cris.virtual.department Universiti Malaysia Perlis
cris.virtualsource.department a22d7e4b-a217-416a-9484-016a3039dc6a
cris.virtualsource.department 41f0fdca-ec0a-443d-9cfe-52d2e51aa4c0
cris.virtualsource.department 9901d4fe-164c-4a44-a60c-445a63ee69d8
cris.virtualsource.department 5303520f-498b-4a26-b983-96d075855646
dc.contributor.author Qaid M.
dc.contributor.author Shafriza Nisha Basah
dc.contributor.author Haniza Yazid
dc.contributor.author Muhammad Juhairi Aziz Safar
dc.contributor.author Mohd Hanafi Mat Som
dc.contributor.author Lim C.C.
dc.date.accessioned 2024-10-01T00:43:05Z
dc.date.available 2024-10-01T00:43:05Z
dc.date.issued 2021-11-25
dc.description.abstract Synthetic data by various algorithms that resemble actual data in terms of statistical features. Computer-aided medical applications have been extensively applied to model specific scenarios, such as medical imaging of retinal images for diabetic retinopathy (DR) detection. The available data and annotated medical data are typically rare and costly due to the difficulties of conducting medical screening and rely on highly trained doctors to review and diagnose. The modelling of retinal images for DR analysis is essential since it will provide a model to guide and test DR detection algorithms. This paper aims to model normal retina and non-proliferative diabetic retinopathy (NPDR) stages (mild, moderate, and severe) data models with the variation of dynamic models. The Digital Retinal Images for Vessel Extraction (DRIVE), The Standard Diabetic Retinopathy Database, Calibration Level 1 (DIARETDB1), and E-OPHTHA datasets are analyzed to obtain the specification of the human retina and DR lesions. In the data modelling phases, the model includes the bright and dark retinal lesions with the variation of dynamic parameters. 4100 synthetic images are used where 200 normal images and 3900 NPDR images to test the performance of DR detection algorithms over the full range of parameters.
dc.identifier.doi 10.1088/1742-6596/2071/1/012047
dc.identifier.scopus 2-s2.0-85122042326
dc.identifier.uri https://hdl.handle.net/20.500.14170/6745
dc.language.iso en
dc.relation.funding Ministry of Higher Education, Malaysia
dc.relation.grantno undefined
dc.relation.ispartof Journal of Physics: Conference Series
dc.relation.ispartofseries Journal of Physics: Conference Series
dc.relation.issn 17426588
dc.rights open access
dc.title Modelling of Retinal Images for Analysis of Diabetic Retinopathy Severity Levels
dc.type Conference Proceeding
dspace.entity.type Publication
oaire.citation.issue 1
oaire.citation.volume 2071
oairecerif.affiliation.orgunit Universiti Malaysia Perlis
oairecerif.affiliation.orgunit Universiti Malaysia Perlis
oairecerif.affiliation.orgunit Universiti Malaysia Perlis
oairecerif.affiliation.orgunit Universiti Malaysia Perlis
oairecerif.affiliation.orgunit Universiti Malaysia Perlis
oairecerif.affiliation.orgunit Universiti Malaysia Perlis
oairecerif.author.affiliation #PLACEHOLDER_PARENT_METADATA_VALUE#
oairecerif.author.affiliation Universiti Malaysia Perlis
oairecerif.author.affiliation Universiti Malaysia Perlis
oairecerif.author.affiliation Universiti Malaysia Perlis
oairecerif.author.affiliation Universiti Malaysia Perlis
oairecerif.author.affiliation #PLACEHOLDER_PARENT_METADATA_VALUE#
oairecerif.citation.number 012047
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person.identifier.scopus-author-id 57391849700
person.identifier.scopus-author-id 26653958200
person.identifier.scopus-author-id 22137274300
person.identifier.scopus-author-id 57212344599
person.identifier.scopus-author-id 57215715847
person.identifier.scopus-author-id 57201525827
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