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Type :article
Subject :QM Human anatomy
ISSN :1424-8220
Main Author :Wang, Shir Li
Additional Authors :Ze, Alexander Hwan Ooi
Zunaina Embong
Aini Ismafairus Abd Hamid
Rafidah Zainon
Theam, Foo Ng
Rostam Affendi Hamzah
Soo, Siang Teoh
Haidi Ibrahim
Title :Interactive blood vessel segmentation from retinal fundus image based on canny edge detector
Place of Production :Tanjong Malim
Publisher :Fakulti Seni, Komputeran dan Industri Kreatif
Year of Publication :2021
Corporate Name :Universiti Pendidikan Sultan Idris
PDF Full Text :Login required to access this item.

Abstract : Universiti Pendidikan Sultan Idris
Optometrists, ophthalmologists, orthoptists, and other trained medical professionals use fundus photography to monitor the progression of certain eye conditions or diseases. Segmentation of the vessel tree is an essential process of retinal analysis. In this paper, an interactive blood vessel segmentation from retinal fundus image based on Canny edge detection is proposed. Semi-automated segmentation of specific vessels can be done by simply moving the cursor across a particular vessel. The pre-processing stage includes the green color channel extraction, applying Contrast Limited Adaptive Histogram Equalization (CLAHE), and retinal outline removal. After that, the edge detection techniques, which are based on the Canny algorithm, will be applied. The vessels will be selected interactively on the developed graphical user interface (GUI). The program will draw out the vessel edges. After that, those vessel edges will be segmented to bring focus on its details or detect the abnormal vessel. This proposed approach is useful because different edge detection parameter settings can be applied to the same image to highlight particular vessels for analysis or presentation.


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