An enhancive Watershed transformation approach to segment Optic Disk from Smartphone Fundus Images

2021 ◽  
Author(s):  
Shubhi Gupta ◽  
Sanjeev Thakur ◽  
Ashutosh Gupta
Keyword(s):  
Optic Disk ◽  
Fundus Images ◽  
Watershed Transformation ◽  
Transformation Approach

Automatic optic disk detection and segmentation by variational active contour estimation in retinal fundus images

2019 ◽  
Vol 13 (6) ◽  
pp. 1191-1198 ◽  
Author(s):  
Syed S. Naqvi ◽  
Nayab Fatima ◽  
Tariq M. Khan ◽  
Zaka Ur Rehman ◽  
M. Aurangzeb Khan
Keyword(s):  
Active Contour ◽  
Optic Disk ◽  
Fundus Images ◽  
Contour Estimation ◽  
Retinal Fundus Images ◽  
Retinal Fundus

CURVELET FUSION ENHACEMENT BASED EVALUATION OF DIABETIC RETINOPATHY BY THE IDENTIFICATION OF EXUDATES IN OPTIC COLOR FUNDUS IMAGES

2016 ◽  
Vol 28 (06) ◽  
pp. 1650046
Author(s):  
V. Ratna Bhargavi ◽  
Ranjan K. Senapati
Keyword(s):  
Diabetic Retinopathy ◽  
Vision Loss ◽  
Detection System ◽  
Clinical Signs ◽  
Posterior Part ◽  
Curvelet Transform ◽  
Optic Disk ◽  
Support Vector ◽  
Fundus Images ◽  
Statistical Measures

Rapid growth of Diabetes mellitus in people causes damage to posterior part of eye vessel structures. Diabetic retinopathy (DR) is an important hurdle in diabetic people and it causes lesion formation in retina due to retinal vessel structures damage. Bright lesions (BLs) or exudates are initial clinical signs of DR. Early BLs detection can help avoiding vision loss. The severity can be recognized based on number of BLs formed in the color fundus image. Manually diagnosing a large amount of images is time consuming. So a computerized DR grading and BLs detection system is proposed. In this paper for BLs detection, curvelet fusion enhancement is done initially because bright objects maps to largest coefficients in an image by utilizing the curvelet transform, so that BLs can be recognized in the retina easily. Then optic disk (OD) appearance is similar to BLs and vessel structures are barriers for lesion exact detection and moreover OD falsely classified as BLs and that increases false positives in classification. So these structures are segmented and eliminated by thresholding techniques. Various features were obtained from detected BLs. Publicly available databases are used for DR severity testing. 260 fundus images were used for the performance evaluation of proposed work. The support vector machine classifier (SVM) used to separate fundus images in various levels of DR based on feature set extracted. The proposed system that obtained the statistical measures were sensitivity 100%, specificity 95.4% and accuracy 97.74%. Compared to existing state-of-art techniques, the proposed work obtained better results in terms of sensitivity, specificity and accuracy.

scholarly journals Automated Segmentation of Optic Disc and Cup in Color Fundus Images

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Vijay M Mane
Keyword(s):  
Optic Disc ◽  
Disease Diagnosis ◽  
Eye Disease ◽  
Automated Segmentation ◽  
Fundus Images ◽  
Average Sensitivity ◽  
Watershed Transformation ◽  
Glaucoma Diagnosis ◽  
Optic Cup ◽  
Color Fundus Images

An automatic Optic disc and Optic cup detection technique which is an important step in developing systems for computer-aided eye disease diagnosis is presented in this paper. This paper presents an algorithm for localization and segmentation of optic disc from digital retinal images. OD localization is achieved by circular Hough transform using morphological preprocessing and segmentation is achieved by watershed transformation. Optic cup segmentation is achieved by marker controlled watershed transformation. The optic disc to cup ratio (CDR) is calculated which is an important parameter for glaucoma diagnosis. The presented algorithm is evaluated against publically available DRIVE dataset. The presented methodology achieved 88% average sensitivity and 80% average overlap. The average CDR detected is 0.1983.

scholarly journals Segmentation of the optic disk in color eye fundus images using an adaptive morphological approach

2010 ◽  
Vol 40 (2) ◽  
pp. 124-137 ◽  
Author(s):  
Daniel Welfer ◽  
Jacob Scharcanski ◽  
Cleyson M. Kitamura ◽  
Melissa M. Dal Pizzol ◽  
Laura W.B. Ludwig ◽  
...  
Keyword(s):  
Optic Disk ◽  
Fundus Images ◽  
Morphological Approach

scholarly journals DETECTION AND SEGMENTATION OF OPTIC DISC IN FUNDUS IMAGES

2018 ◽  
Vol 10 (5) ◽  
pp. 20
Author(s):  
Ramesh C. ◽  
Udayakumar E. ◽  
Yogeshwaran K.
Keyword(s):  
Image Processing ◽  
Optic Disc ◽  
Retinal Image ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Optic Disk ◽  
Curve Evolution ◽  
Fundus Images ◽  
Medical Field ◽  
Shape And Size

Objective: Image processing technique is utilized in the medical field widely nowadays. Hence, therefore, this technique is used to extract the different features like blood vessels, optic disk, macula, fovea etc. automatically of the retinal image of eye.Methods: This paper presents a simple and fast algorithm using Mathematical Morphology to find the fovea of fundus retinal image. The image for analysis is obtained from the DRIVE database. Also, this paper is enhanced to detect the Diabetic Retinopathy disease occurring in the eye.Results: Detection of optic disc boundary becomes important for the diagnosis of glaucoma. The iterative curve evolution was stopped at the image boundaries where the energy was minimum.Conclusion: The changes in the shape and size of the optic disc can be used to detect glaucoma and also cup ratio can be used as a measure of glaucoma.

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