Universiti Teknologi Malaysia Institutional Repository

Preprocessing digital retinal images for vessel segmentation

Tan, Tian-Swee and Ameen, Nurul Emaan and Wan Hitam, Wan Hazabah and Hum, Yan-Chai and Teoh, Chong-Keat (2017) Preprocessing digital retinal images for vessel segmentation. Research Journal of Applied Sciences, Engineering and Technology, 14 (1). pp. 1-6. ISSN 2040-7459


Official URL: https://dx.doi.org/10.19026/rjaset.14.3982


The information contained in the retinal vasculature is used to diagnose the onset of retinal diseases such as diabetic retinopathy. However, due to non-uniform illumination and variations in imaging modalities, the contrast between the retinal blood vessels network and the background is very low, encumbering the analysis and the diagnosis processes. This prompts the need for preprocessing digital fundus images to remove noise and improve contrast thus increasing the segmentation accuracy of the retinal vasculature. In this study, we address issues of nonuniform illumination and low contrast by developing a framework that implements shade correction, image enhancement and prepares the digital fundus images for the next stage.

Item Type:Article
Uncontrolled Keywords:Binary mask generation, contrast enhancement, morphological operations, retinal fundus images
Subjects:Q Science > QH Natural history > QH301 Biology
Divisions:Biosciences and Medical Engineering
ID Code:80462
Deposited By: Fazli Masari
Deposited On:22 May 2019 06:45
Last Modified:22 May 2019 06:45

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