Computerized screening of diabetic retinopathy employing blood vessel segmentation in retinal images

Franklin, S. Wilfred; Rajan, S. Edward

doi:10.1016/j.bbe.2014.01.004

Cited by 122 publications

(45 citation statements)

References 22 publications

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“…Hence segmentation of blood vessels in the fundus image and further analysis of its properties aids in diagnosis of retinal vascular disorders. Also, segmentation of blood vessels and hence extraction of vascular points is useful for image registration [3]. Even for people with expertise, segmentation of blood vessels is a time consuming and effort prone process.…”

Section: Introductionmentioning

confidence: 99%

“…It is a high frequency component exhibited more clearly at high contrast. The retinal blood vessels are one of the most important structures of the retina providing blood supply to the retina and also transmitting the information signals from the retina to the brain [3].…”

Section: Introductionmentioning

confidence: 99%

“…This method processes an image in less than 90 s due to its simplicity of operation. Again, Franklin et al [3] made an attempt using neural networks to segment retinal vessels, through a feature vector formed using the intensities of red, green and blue channels of the RGB image yielding an accuracy of 95.03%.…”

mentioning

confidence: 99%

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Retinal blood vessel segmentation employing image processing and data mining techniques for computerized retinal image analysis

GeethaRamani

Balasubramanian

2016

Biocybernetics and Biomedical Engineering

110

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Retinal blood vessel segmentation employing image processing and data mining techniques for computerized retinal image analysis

GeethaRamani

Balasubramanian

2016

Biocybernetics and Biomedical Engineering

110

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“…This method gives good performance in classify artery and vein but its performance may be different in other cases. In the other research, Wilfred et al [66] used backpropagation neural network to classify pixel of retinal image into vessel and non-vessel. It ensures the best performance in the classification stage.…”

Section: Neural Networkmentioning

confidence: 99%

Segmentation of retinal blood vessels for detection of diabetic retinopathy: A review

Aras¹,

Lestari²,

Nugroho³

et al. 2016

CST

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Diabetic detinopathy (DR) is effect of diabetes mellitus to the human vision that is the major cause of blindness. Early diagnosis of DR is an important requirement in diabetes treatment. Retinal fundus image is commonly used to observe the diabetic retinopathy symptoms. It can present retinal features such as blood vessel and also capture the pathologies which may lead to DR. Blood vessel is one of retinal features which can show the retina pathologies. It can be extracted from retinal image by image processing with following stages: preprocessing, segmentation, and post-processing. This paper contains a review of public retinal image dataset and several methods from various conducted researches. All discussed methods are applicable to each researcher cases. There is no further analysis to conclude the best method which can be used for general cases. However, we suggest morphological and multiscale method that gives the best accuracy in segmentation.

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“…Franklin et al [17] proposed a method to recognize the retinal blood vessels with the help of multilayer perceptron neural network. In this procedure, the input is derived from the three colour components, i.e., red, green and blue.…”

Section: International Journal Of Computer Applications (0975 -8887) mentioning

confidence: 99%

Localization of Optic Disc and Blood Vessel Segmentation: A Survey

Bharathan¹,

Anjali²,

Remya³

2017

IJCA

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Nowadays, number of retinal disorders are affecting to all age groups. Various research activities are being carried out to diagnosis the disorders. Damage to retina leads to loss of vision. An efficient detection of optic disc(OD) is an important task in an automated retinal image examination system. Most of the OD detection algorithms are developed for normal retinal images. So, to detect OD from normal, healthy and abnormal retinal images are challenging tasks. In this work, the various methods used to locate OD and blood vessel segmentation from retinal images are discussed.

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Computerized screening of diabetic retinopathy employing blood vessel segmentation in retinal images

Cited by 122 publications

References 22 publications

Retinal blood vessel segmentation employing image processing and data mining techniques for computerized retinal image analysis

Retinal blood vessel segmentation employing image processing and data mining techniques for computerized retinal image analysis

Segmentation of retinal blood vessels for detection of diabetic retinopathy: A review

Localization of Optic Disc and Blood Vessel Segmentation: A Survey

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