Supervised pterygium fibrovascular redness grading using generalized regression neural network
Pterygium is a growth on the eye that can cause blindness, with countries closer to the equator showing higher rate of incidence. However, there is a lack of research to study the severity and properties of the tissue. We propose the use of Generalized Neural Network (GRNN) to objectively...
| Main Authors: | , , |
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| Format: | Proceeding Paper |
| Language: | English English |
| Published: |
IOS Press
2014
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/40795/ http://irep.iium.edu.my/40795/7/40795%20Supervised%20pterygium%20fibrovascular%20redness%20grading.pdf http://irep.iium.edu.my/40795/8/40795%20Supervised%20pterygium%20fibrovascular%20redness%20grading%20SCOPUS.pdf |
| _version_ | 1848782010908147712 |
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| author | Che Azemin, Mohd Zulfaezal Hilmi, Mohd. Radzi Mohd. Kamal, Khairidzan |
| author_facet | Che Azemin, Mohd Zulfaezal Hilmi, Mohd. Radzi Mohd. Kamal, Khairidzan |
| author_sort | Che Azemin, Mohd Zulfaezal |
| building | IIUM Repository |
| collection | Online Access |
| description | Pterygium is a growth on the eye that can cause blindness, with countries closer to the equator showing higher rate of incidence. However, there is a lack of research to study the severity and properties of the tissue. We propose the use of Generalized Neural Network (GRNN) to objectively quantify redness of the fibrovascular tissue. Comparative analysis using multiple feature selection algorithms indicates that error can be minimized when use with optimal set of features and suitable GRNN spread parameter. Features nominated by Minimum Redundancy Maximum Relevance gives the best performance with SSE = 3.55 and GRNN spread = 0.47. |
| first_indexed | 2025-11-14T15:58:40Z |
| format | Proceeding Paper |
| id | iium-40795 |
| institution | International Islamic University Malaysia |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-14T15:58:40Z |
| publishDate | 2014 |
| publisher | IOS Press |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | iium-407952019-05-28T01:06:37Z http://irep.iium.edu.my/40795/ Supervised pterygium fibrovascular redness grading using generalized regression neural network Che Azemin, Mohd Zulfaezal Hilmi, Mohd. Radzi Mohd. Kamal, Khairidzan RE Ophthalmology TA164 Bioengineering Pterygium is a growth on the eye that can cause blindness, with countries closer to the equator showing higher rate of incidence. However, there is a lack of research to study the severity and properties of the tissue. We propose the use of Generalized Neural Network (GRNN) to objectively quantify redness of the fibrovascular tissue. Comparative analysis using multiple feature selection algorithms indicates that error can be minimized when use with optimal set of features and suitable GRNN spread parameter. Features nominated by Minimum Redundancy Maximum Relevance gives the best performance with SSE = 3.55 and GRNN spread = 0.47. IOS Press 2014 Proceeding Paper PeerReviewed application/pdf en http://irep.iium.edu.my/40795/7/40795%20Supervised%20pterygium%20fibrovascular%20redness%20grading.pdf application/pdf en http://irep.iium.edu.my/40795/8/40795%20Supervised%20pterygium%20fibrovascular%20redness%20grading%20SCOPUS.pdf Che Azemin, Mohd Zulfaezal and Hilmi, Mohd. Radzi and Mohd. Kamal, Khairidzan (2014) Supervised pterygium fibrovascular redness grading using generalized regression neural network. In: 13th International Conference on New Trends in Intelligent Software Methodology Tools, and Techniques (SoMeT_14), 22nd-24th September 2014, Langkawi, Kedah, Malaysia. http://ebooks.iospress.nl/volumearticle/37350 10.3233/978-1-61499-434-3-650 |
| spellingShingle | RE Ophthalmology TA164 Bioengineering Che Azemin, Mohd Zulfaezal Hilmi, Mohd. Radzi Mohd. Kamal, Khairidzan Supervised pterygium fibrovascular redness grading using generalized regression neural network |
| title | Supervised pterygium fibrovascular redness grading using generalized regression neural network |
| title_full | Supervised pterygium fibrovascular redness grading using generalized regression neural network |
| title_fullStr | Supervised pterygium fibrovascular redness grading using generalized regression neural network |
| title_full_unstemmed | Supervised pterygium fibrovascular redness grading using generalized regression neural network |
| title_short | Supervised pterygium fibrovascular redness grading using generalized regression neural network |
| title_sort | supervised pterygium fibrovascular redness grading using generalized regression neural network |
| topic | RE Ophthalmology TA164 Bioengineering |
| url | http://irep.iium.edu.my/40795/ http://irep.iium.edu.my/40795/ http://irep.iium.edu.my/40795/ http://irep.iium.edu.my/40795/7/40795%20Supervised%20pterygium%20fibrovascular%20redness%20grading.pdf http://irep.iium.edu.my/40795/8/40795%20Supervised%20pterygium%20fibrovascular%20redness%20grading%20SCOPUS.pdf |