Accurate detection of blood vessels improves the detection of exudates in color fundus images

Youssef, Doaa; Solouma, Nahed H.

doi:10.1016/j.cmpb.2012.06.006

Cited by 57 publications

(15 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Youssef and Solouma in 2012 have applied [26] robust algorithm for determining BVs and EXs in fundus images using image processing algorithms. It can be fully automatic or semi-automatic.…”

Section: Ganesan Et Al In 2015 Have Extractedmentioning

confidence: 99%

Unravelling Diabetic Retinopathy Through Image Processing, Neural Networks and Fuzzy Logic – A Review

Srinivasan

Sudha²

2017

Asian J Pharm Clin Res

View full text Add to dashboard Cite

One of the main causes of blindness is diabetic retinopathy (DR) and it may affect people of any ages. In these days, both young and old ages are affected by diabetes, and the di abetes is the main cause of DR. Hence, it is necessary to have an automated system with good accuracy and less computation time to diagnose and treat DR, and the automated system can simplify the work of ophthalmologists. The objective is to present an overview of various works recently in detecting and segmenting the various lesions of DR. Papers were categorized based on the diagnosing tools and the methods used for detecting early and advanced stage lesions. The early lesions of DR are microaneurysms, hemorrhages, exudates, and cotton wool spots and in the advanced stage, new and fragile blood vessels can be grown. Results have been evaluated in terms of sensitivity, specificity, accuracy and receiver operating characteristic curve. This paper analyzed the various steps and different algorithms used recently for the detection and classification of DR lesions. A comparison of performances has been made in terms of sensitivity, specificity, area under the curve, and accuracy. Suggestions, future workand the area to be improved were also discussed.Keywords: Diabetic retinopathy, Image processing, Morphological operations, Neural network, Fuzzy logic.

show abstract

“…Youssef and Solouma in 2012 have applied [26] robust algorithm for determining BVs and EXs in fundus images using image processing algorithms. It can be fully automatic or semi-automatic.…”

Section: Ganesan Et Al In 2015 Have Extractedmentioning

confidence: 99%

Unravelling Diabetic Retinopathy Through Image Processing, Neural Networks and Fuzzy Logic – A Review

Srinivasan

Sudha²

2017

Asian J Pharm Clin Res

View full text Add to dashboard Cite

show abstract

“…An association between retinal vessel diameter and cardiovascular mortality was found [2]. Furthermore, it is stated [3] that detection of blood vessels can improve the detection of exudates in a color fundus image. While detecting vascular trees can reveal useful information for the diagnosis of various diseases such as hypertension, diabetes, and glaucoma [4], an accurate detection result can also be used for locating the optic disc [5].…”

Section: Introductionmentioning

confidence: 97%

Retinal vessel segmentation using modified symmetrical local threshold

Özgünalp¹

2020

Turk J Elec Eng & Comp Sci

View full text Add to dashboard Cite

Retinal vessel segmentation is important for the identification of many diseases including glaucoma, hypertensive retinopathy, diabetes, and hypertension. Moreover, retinal vessel diameter is associated with cardiovascular mortality. Accurate detection of blood vessels improves the detection of exudates in color fundus images, as well as detection of the retinal nerve, optic disc, or fovea. A retinal vessel is a darker stripe on a lighter background. Thus, the objective is very similar to the lane detection task for intelligent vehicles. A lane on a road is a light stripe on a darker background (i.e. asphalt). For lane detection, the symmetrical local threshold (SLT) is found to be the most robust feature extractor among the tested algorithms in the road marking (ROMA) dataset. Unfortunately, the SLT cannot be applied directly for retinal vessel segmentation. The SLT is a 1D filter and is designed for detecting vertical or close to vertical light stripes with predictable width. In this paper, the SLT is modified to detect dark stripes and four kernels, instead of one, are designed to detect both vertical and horizontal features of a retinal vessel with variable thickness. The proposed algorithm is tested using the High Resolution Fundus (HRF) image database and the accuracy is estimated to be 95.53%. Furthermore, when tested with the Digital Retinal Images for Vessel Segmentation (DRIVE) database, the accuracy is estimated to be 93.69% .

show abstract

“…This methodology got promising outcomes with respect to affectability and identity. The course adaboost classifier was proposed by Cheng and Jhan [29]. They united it with Support Vector Machine (SVM) and adaboost, and a continuous individual by walking acknowledgment structure with a single camera.…”

Section: Introductionmentioning

confidence: 99%

A Novel Approach for Detection of Diabetic Retinopathy using the Concept of Computer Vision

Singh¹

2019

IJRASET

View full text Add to dashboard Cite

Diabetic retinopathy (DR) and diabetic macular edema are basic confusions of diabetes which can prompt vision misfortune. The reviewing of DR is a genuinely mind boggling process that requires the discovery of fine highlights, for example, micro aneurysms, intraregional hemorrhages, and intraregional micro vascular anomalies. Along these lines, there can be a decent measure of grader fluctuation. There are distinctive techniques for acquiring the reference standard and settling contradictions among graders, and keeping in mind that it is generally acknowledged that mediation until full accord will yield the best reference standard, the contrast between different strategies for settling differences has not been inspected broadly. According to the extending use of sugar materials in human life and creating example of the machine life, the prevalence of diabetes is on the rising. It is observed all patients with this affliction for the most part experience the evil impacts of decrease or mishap their vision. For the modified examination of diabetic retinopathy (DR) and affirmation of a diabetic eye from a sound eye. In this paper basically we proposed an approach where we try to find the diabetic retinopathy by using of the human retina eye. In this work basically we did the comparative analysis for the healthy eye and diabetic retinopathy eye. As per the result our proposed approach performs well as compare to previous existing approach

show abstract

Accurate detection of blood vessels improves the detection of exudates in color fundus images

Cited by 57 publications

References 11 publications

Unravelling Diabetic Retinopathy Through Image Processing, Neural Networks and Fuzzy Logic – A Review

Unravelling Diabetic Retinopathy Through Image Processing, Neural Networks and Fuzzy Logic – A Review

Retinal vessel segmentation using modified symmetrical local threshold

A Novel Approach for Detection of Diabetic Retinopathy using the Concept of Computer Vision

Contact Info

Product

Resources

About