Automatic Detection of Blood Vessel in Retinal Images

Elbalaoui, Abderrahmane; Fakir, Mohamed; Taifi, Khaddouj; Merbouha, Abdelkrim

doi:10.1109/cgiv.2016.69

Cited by 28 publications

(21 citation statements)

References 10 publications

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“…The Vessels are detected using Otsus method. Once the vessels are separated, the following step is to separate out the arteries and the veins [10] [11]. The branch junction are detected and subtracted from the vessel detected image.…”

Section: Proposed Ideamentioning

confidence: 99%

An Elementary Method for the Computation of Artery to Vein Ratio in Fundus Images

Savant¹

2019

IJRASET

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Medical research has shown that the artery to vein ratio can be used to detect Hypertensive Retinopathy. This ratio can be calculated by carefully studying the fundus images of the patients. Modern softwares can be used to process these images. This article will describe a simple method to compute the ratio of mean artery width to mean vein width. The images for testing of the described method have been taken from local eye clinic run by Althea Barbosa, Goa and few have been collected from online database STARE and DRIVE.

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Section: Proposed Ideamentioning

confidence: 99%

An Elementary Method for the Computation of Artery to Vein Ratio in Fundus Images

Savant¹

2019

IJRASET

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“…Every fundus image is processed with a different intensity threshold value for more accurate detection. Elbalaoui, A., et al [2016] developed the automatic detection of blood vessel in the retinal images. This paper proposes the automatic detection of the retinal blood vessels and the measurement of the vessel diameter.…”

Section: Introductionmentioning

confidence: 99%

“…This paper proposes the automatic detection of the retinal blood vessels and the measurement of the vessel diameter. In which it is important for the diagnosis and the treatment of different ocular diseases including DR, glaucoma and hypertension [2].The proposed method consists of three main steps: Pre-processing of retinal images, the Vesselness filter is used to enhance the blood vessels and Finally Hessian multi-scale enhancement filter is designed from the adaptive thresholding of the output of a vesselness filter for vessels detection.…”

Section: Introductionmentioning

confidence: 99%

Diabetic Retinopathy Detection using Image Processing

Naveen,

Sivakumar,

Shankar

et al. 2019

IJEAT

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The main objective of this method is to detect DR (Diabetic Retinopathy) eye disease using Image Processing techniques. The tool used in this method is MATLAB (R2010a) and it is widely used in image processing. This paper proposes a method for Extraction of Blood Vessels from the medical image of human eye-retinal fundus image that can be used in ophthalmology for detecting DR. This method utilizes an approach of Adaptive Histogram Equalization using CLAHE (Contrast Limited Adaptive Histogram Equalization) algorithm with open CV (Computer Vision) framework implementation. The result shows that affected DR is detected in fundus image and the DR is not detected in the healthy fundus image and 98% of Accuracy can be achieved in the detection of DR.

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“…Saleh et al [18] identified that green channel generates maximum contrast on retina image, thus differentiating one feature to the other. In reserach of Patwari et al [19] green channel shows higher contrast intensity compared with red and blue channel, while Elbalaoui et al [20] said that green channel has the best contrast compared with the red and blue channels.…”

Section: Green Channelmentioning

confidence: 99%

“…in CLAHE, contrast limitation is applied to every pixel to avoid noise amplication. Elbalaoui et al [20] used CLAHE because it can increase the contrast between contours. When enhancing the contrast image, two factors must be considered, spped and efficiency.…”

Section: Histogram Equalizationmentioning

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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Automatic Detection of Blood Vessel in Retinal Images

Cited by 28 publications

References 10 publications

An Elementary Method for the Computation of Artery to Vein Ratio in Fundus Images

An Elementary Method for the Computation of Artery to Vein Ratio in Fundus Images

Diabetic Retinopathy Detection using Image Processing

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

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