Extraction and reconstruction of retinal vasculature

Fadzil, M.H.A. and Izhar, L.I. and Venkatachalam, P.A. and Karunakar, T.V.N. (2007) Extraction and reconstruction of retinal vasculature. Journal of Medical Engineering and Technology, 31 (6). pp. 435-442. ISSN 03091902

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Abstract

Information about retinal vasculature morphology is used in grading the severity and progression of diabetic retinopathy. An image analysis system can help ophthalmologists make accurate and efficient diagnoses. This paper presents the development of an image processing algorithm for detecting and reconstructing retinal vasculature. The detection of the vascular structure is achieved by image enhancement using contrast limited adaptive histogram equalization followed by the extraction of the vessels using bottom-hat morphological transformation. For reconstruction of the complete retinal vasculature, a region growing technique based on first-order Gaussian derivative is developed. The technique incorporates both gradient magnitude change and average intensity as the homogeneity criteria that enable the process to adapt to intensity changes and intensity spread over the vasculature region. The reconstruction technique reduces the required number of seeds to near optimal for the region growing process. It also overcomes poor performance of current seed-based methods, especially with low and inconsistent contrast images as normally seen in vasculature regions of fundus images. Simulations of the algorithm on 20 test images from the DRIVE database show that it outperforms many other published methods and achieved an accuracy range (ability to detect both vessel and non-vessel pixels) of 0.91-0.95, a sensitivity range (ability to detect vessel pixels) of 0.91-0.95 and a specificity range (ability to detect non-vessel pixels) of 0.88-0.94. © 2007 Informa UK Ltd.

Item Type: Article
Additional Information: cited By 18
Uncontrolled Keywords: Algorithms; Blood vessels; Feature extraction; Image analysis; Image enhancement; Ophthalmology, Gaussian derivative; Region growing; Retinal vasculature detection and reconstruction, Biomedical engineering, accuracy; article; contrast enhancement; data base; eye fundus; histogram; image enhancement; image processing; imaging system; ocular blood vessel; plastic surgery; retina; sensitivity analysis; simulation; surgical technique, Humans; Image Enhancement; Image Interpretation, Computer-Assisted; Pattern Recognition, Automated; Reproducibility of Results; Retinal Vessels; Retinoscopy; Sensitivity and Specificity
Depositing User: Mr Ahmad Suhairi UTP
Date Deposited: 09 Nov 2023 15:15
Last Modified: 09 Nov 2023 15:15
URI: https://khub.utp.edu.my/scholars/id/eprint/236

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