Measuring morphologic properties of the human retinal vessel system using a two-stage image processing approach

Kaupp, A.; Dölemeyer, Arno; Wilzeck, R.; Schlosser, Ralf W.; Wolf, Sebastián; Meyer‐Ebrecht, D.

doi:10.1109/icip.1994.413350

Cited by 10 publications

(3 citation statements)

References 6 publications

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“…It has been investigated as a precursor for other issues, for example as identifying a starting point for blood vessel segmentation [23], [24]. It has also been investigated as a byproduct of general retinal image segmentation, for instance into separate identifications of arteries, veins, the nerve, the fovea, and lesions [1], [7], [13], [17]. Here, we review these related works.…”

Section: A Related Workmentioning

confidence: 99%

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Locating the optic nerve in a retinal image using the fuzzy convergence of the blood vessels

Hoover

Goldbaum

2003

IEEE Trans. Med. Imaging

689

319

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Abstract-We describe an automated method to locate the optic nerve in images of the ocular fundus. Our method uses a novel algorithm we call fuzzy convergence to determine the origination of the blood vessel network. We evaluate our method using 31 images of healthy retinas and 50 images of diseased retinas, containing such diverse symptoms as tortuous vessels, choroidal neovascularization, and hemorrhages that completely obscure the actual nerve. On this difficult data set, our method achieved 89% correct detection. We also compare our method against three simpler methods, demonstrating the performance improvement. All our images and data are freely available for other researchers to use in evaluating related methods.

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Section: A Related Workmentioning

confidence: 99%

“…In [13], a method is presented to segment a retinal image into arteries, veins, the optic disk, the macula, and background. The method is based upon split-and-merge segmentation, followed by feature based classification.…”

Section: A Related Workmentioning

confidence: 99%

Locating the optic nerve in a retinal image using the fuzzy convergence of the blood vessels

Hoover

Goldbaum

2003

IEEE Trans. Med. Imaging

689

319

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“…Tracing of vessels is done via forward detection, bifurcation identification, and backward verification. In the work done by A.Kaupp et.al, a method was presented to segment a retinal image into arteries, veins, the optic disk, the macula, and background [4]. The method is based upon split-and-merge segmentation, followed by feature based classification.…”

Section: Introductionmentioning

confidence: 99%

Detection of exudates and feature extraction of retinal images using fuzzy clustering method

Princye¹,

Vijayakumari²

2013

Third International Conference on Computational Intelligence and Information Technology (CIIT 2013)

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Diabetic retinopathy (DR) is the micro vascular changes that cause detectable changes in the optic disc. This paper aims at the detection of retinal exudates and other features such as blood vessels and optic disc from fundus image. The two methods are implemented for the detection of exudates they are morphological method and FCM clustering method. Contrast limited adaptive histogram equalization (CLACHE) is used to extract the green component in the image. In blood vessel extraction, blood vessels are extracted by top hat transformation followed by connected component analysis. The optic disc centre is found using Circular Hough Transform (CHT) and propagation through radii method is employed and the entire optic disc region is blackened and removed. Exudates detection is the important characteristics of diabetic retinopathy and its varies depends upon the severity of the DR. The FCM method used to detect exudates. The overall sensitivity, specificity and accuracy are calculated and 98% accuracy obtained

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Automatic Localization and Segmentation of Blood Vessels, Optic Disc, and Macula in Digital Fundus Images

Balasubramanian

Sagar

Saradhi

et al. 2008

Lecture Notes in Electrical Engineering

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Measuring morphologic properties of the human retinal vessel system using a two-stage image processing approach

Cited by 10 publications

References 6 publications

Locating the optic nerve in a retinal image using the fuzzy convergence of the blood vessels

Locating the optic nerve in a retinal image using the fuzzy convergence of the blood vessels

Detection of exudates and feature extraction of retinal images using fuzzy clustering method

Automatic Localization and Segmentation of Blood Vessels, Optic Disc, and Macula in Digital Fundus Images

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