Retinal Width Estimation of High-Resolution Fundus Images For Diabetic Retinopathy Detection

Citation

Ali, Aziah and Wan Zaki, Wan Mimi Diyana and Hussain, Aini and Wan Abdul Halim, Wan Haslina (2021) Retinal Width Estimation of High-Resolution Fundus Images For Diabetic Retinopathy Detection. In: 2020 IEEE EMBS Conference on Biomedical Engineering and Sciences, IECBES 2020, 1 - 3 Mar 2021, Langkawi, Malaysia.

[img] Text
Retinal Width Estimation of High-Resolution Fundus Images....pdf
Restricted to Repository staff only

Download (900kB)

Abstract

Studies have shown some correlations between retinal vessel morphologies and multiple systemic diseases. While this could pave the way to timely diagnosis of such diseases by examining vessels from fundus images, practical application of measuring and quantifying changes in vessel width over time remains a challenge. In this study, we propose a semi-automated estimation method to efficiently summarize vessel width characteristics from fundus images. The method consists of retinal vessel segmentation, optic disc (OD) localization and vessel width parameters estimation. The proposed method is validated using a public database of high-resolution fundus images called HRF, where the significance of obtained vessel width parameters in differentiating the three image groups in the database are analysed. Results indicate that the obtained parameter using the method that summarises the ratio between width of veins to arteries, AVR (Artery-Vein Ratio) can be used to differentiate images from patients with Diabetic Retinopathy against healthy and glaucomatous patients.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: High resolution imaging
Subjects: T Technology > TA Engineering (General). Civil engineering (General) > TA1501-1820 Applied optics. Photonics
Divisions: Faculty of Computing and Informatics (FCI)
Depositing User: Ms Nurul Iqtiani Ahmad
Date Deposited: 30 Jun 2021 16:20
Last Modified: 30 Jun 2021 16:20
URII: http://shdl.mmu.edu.my/id/eprint/8786

Downloads

Downloads per month over past year

View ItemEdit (login required)