Glaucoma detection of retinal images based on boundary segmentation
The rapid growth of technology makes it possible to implement in immediate diagnosis for patients using image processing. By using morphological processing and adaptive thresholding method for segmentation of optic disc and optic cup, various sizes of retinal fundus images captured through fundus ca...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Institute of Advanced Engineering and Science IAES
2020
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| Online Access: | http://eprints.uthm.edu.my/5282/1/AJ%202020%20%28138%29.pdf |
| _version_ | 1796869174529622016 |
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| author | Zainudin, Noraina Alia Nazari, Ain Mustafa, Mohd Marzuki Wan Zakaria, Wan NurShazwani Suriani, Nor Surayahani Wan Kairuddin, Wan Nur Hafsha |
| author_facet | Zainudin, Noraina Alia Nazari, Ain Mustafa, Mohd Marzuki Wan Zakaria, Wan NurShazwani Suriani, Nor Surayahani Wan Kairuddin, Wan Nur Hafsha |
| author_sort | Zainudin, Noraina Alia |
| collection | UTHM |
| description | The rapid growth of technology makes it possible to implement in immediate diagnosis for patients using image processing. By using morphological processing and adaptive thresholding method for segmentation of optic disc and optic cup, various sizes of retinal fundus images captured through fundus camera from online databases can be processed. This paper explains the use of color channel separation method for pre-processing to remove noise for better optic disc and optic cup segmentation. Noise removal will improve image quality and in return help to increase segmentation standard. Then, morphological processing and adaptive thresholding method is used to extract out optic disc and optic cup from fundus image. The proposed method is tested on two publicly available online databases: RIM-ONE and DRIONS-DB. On RIM-ONE database, the average PSNR value acquired is 0.01891 and MSE is 65.62625. Meanwhile, for DRIONS-DB database, the best PSNR is 64.0928 and the MSE is 0.02647. In conclusion, the proposed method can successfully filter out any unwanted noise in the image and are able to help clearer optic disc and optic cup segmentation to be performed. |
| first_indexed | 2024-03-05T21:50:54Z |
| format | Article |
| id | uthm.eprints-5282 |
| institution | Universiti Tun Hussein Onn Malaysia |
| language | English |
| last_indexed | 2024-03-05T21:50:54Z |
| publishDate | 2020 |
| publisher | Institute of Advanced Engineering and Science IAES |
| record_format | dspace |
| spelling | uthm.eprints-52822022-01-09T01:45:43Z http://eprints.uthm.edu.my/5282/ Glaucoma detection of retinal images based on boundary segmentation Zainudin, Noraina Alia Nazari, Ain Mustafa, Mohd Marzuki Wan Zakaria, Wan NurShazwani Suriani, Nor Surayahani Wan Kairuddin, Wan Nur Hafsha T Technology (General) TA1501-1820 Applied optics. Photonics The rapid growth of technology makes it possible to implement in immediate diagnosis for patients using image processing. By using morphological processing and adaptive thresholding method for segmentation of optic disc and optic cup, various sizes of retinal fundus images captured through fundus camera from online databases can be processed. This paper explains the use of color channel separation method for pre-processing to remove noise for better optic disc and optic cup segmentation. Noise removal will improve image quality and in return help to increase segmentation standard. Then, morphological processing and adaptive thresholding method is used to extract out optic disc and optic cup from fundus image. The proposed method is tested on two publicly available online databases: RIM-ONE and DRIONS-DB. On RIM-ONE database, the average PSNR value acquired is 0.01891 and MSE is 65.62625. Meanwhile, for DRIONS-DB database, the best PSNR is 64.0928 and the MSE is 0.02647. In conclusion, the proposed method can successfully filter out any unwanted noise in the image and are able to help clearer optic disc and optic cup segmentation to be performed. Institute of Advanced Engineering and Science IAES 2020 Article PeerReviewed text en http://eprints.uthm.edu.my/5282/1/AJ%202020%20%28138%29.pdf Zainudin, Noraina Alia and Nazari, Ain and Mustafa, Mohd Marzuki and Wan Zakaria, Wan NurShazwani and Suriani, Nor Surayahani and Wan Kairuddin, Wan Nur Hafsha (2020) Glaucoma detection of retinal images based on boundary segmentation. Indonesian Journal of Electrical Engineering and Computer Science, 18 (1). pp. 377-384. ISSN 2502-4752 https://dx.doi.org/10.11591/ijeecs.v18.i1.pp377-384 |
| spellingShingle | T Technology (General) TA1501-1820 Applied optics. Photonics Zainudin, Noraina Alia Nazari, Ain Mustafa, Mohd Marzuki Wan Zakaria, Wan NurShazwani Suriani, Nor Surayahani Wan Kairuddin, Wan Nur Hafsha Glaucoma detection of retinal images based on boundary segmentation |
| title | Glaucoma detection of retinal images based on boundary segmentation |
| title_full | Glaucoma detection of retinal images based on boundary segmentation |
| title_fullStr | Glaucoma detection of retinal images based on boundary segmentation |
| title_full_unstemmed | Glaucoma detection of retinal images based on boundary segmentation |
| title_short | Glaucoma detection of retinal images based on boundary segmentation |
| title_sort | glaucoma detection of retinal images based on boundary segmentation |
| topic | T Technology (General) TA1501-1820 Applied optics. Photonics |
| url | http://eprints.uthm.edu.my/5282/1/AJ%202020%20%28138%29.pdf |
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