Che Azemin, Mohd Zulfaezal and Mohd Tamrin, Mohd Izzuddin (2025) Optimized retinal vessel segmentation using IS-Net and high-resolution dataset. In: 2nd International Conference on Data, Information and Computing Science (CDICS 2024), 6th - 8th December 2024, Singapore.
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Abstract
Segmentation of the retinal vessels is extremely useful and very important in the diagnosis and management of various diseases associated with the eye, including diabetic retinopathy and glaucoma. The work has presented an improved methodology using an IS-Net model trained on the high-resolution FIVES dataset, including 800 annotated images of the retina. This paper therefore resolves the proposed approach by pre-processing, which consists of normalizing and performing horizontal flipping, followed by enhancement using IS-Net and histogram-based thresholding criteria for vessel structure binarization. The IS-Net architecture is designed with multi-scale RSU blocks to capture both fine and broad vessel details comprehensively for segmentation. Results have shown that IS-Net achieves a good balance in recall and specificity, with the F1 score high enough to outperform other models in terms of specificity by reducing false positives. These findings underlined the effectiveness of IS-Net for clinical applications and emphasized the value of high-resolution data for refinement in the performance of segmentation.
| Item Type: | Proceeding Paper (Other) |
|---|---|
| Additional Information: | 6768/119705 |
| Uncontrolled Keywords: | Retinal vessel segmentation, IS-Net, high-resolution fundus imaging, FIVES dataset, Otsu's thresholding, deep learning, medical image analysis, encoderdecoder architecture, RSU blocks, ophthalmic diagnostics, vessel enhancement, specificity, recall, automated diagnosis, pixel-wise annotation |
| Subjects: | R Medicine > R Medicine (General) T Technology > T Technology (General) |
| Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): | Kulliyyah of Allied Health Sciences Kulliyyah of Information and Communication Technology Kulliyyah of Information and Communication Technology |
| Depositing User: | Dr. Mohd Zulfaezal Che Azemin |
| Date Deposited: | 25 Feb 2025 12:01 |
| Last Modified: | 25 Feb 2025 12:04 |
| URI: | http://irep.iium.edu.my/id/eprint/119705 |
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