scholarly journals Contrast based circular approximation for accurate and robust optic disc segmentation in retinal images

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e3763 ◽  
Author(s):  
Jose Sigut ◽  
Omar Nunez ◽  
Francisco Fumero ◽  
Marta Gonzalez ◽  
Rafael Arnay
Keyword(s):  
Optic Disc ◽  
Detection Rate ◽  
State Of The Art ◽  
Retinal Images ◽  
Disc Center ◽  
Circular Model ◽  
Starting Point ◽  
Optic Disc Localization ◽  
Average Contrast ◽  
Overlap Coefficient

A new method for automatic optic disc localization and segmentation is presented. The localization procedure combines vascular and brightness information to provide the best estimate of the optic disc center which is the starting point for the segmentation algorithm. A detection rate of 99.58% and 100% was achieved for the Messidor and ONHSD databases, respectively. A simple circular approximation to the optic disc boundary is proposed based on the maximum average contrast between the inner and outer ring of a circle centered on the estimated location. An average overlap coefficient of 0.890 and 0.865 was achieved for the same datasets, outperforming other state of the art methods. The results obtained confirm the advantages of using a simple circular model under non-ideal conditions as opposed to more complex deformable models.

Automatic optic disc localization and segmentation in retinal images by a line operator and level sets

2016 ◽  
Vol 24 (s2) ◽  
pp. S767-S776 ◽  
Author(s):  
Fulong Ren ◽  
Wei Li ◽  
Jinzhu Yang ◽  
Huan Geng ◽  
Dazhe Zhao
Keyword(s):  
Optic Disc ◽  
Level Sets ◽  
Retinal Images ◽  
Optic Disc Localization ◽  
Line Operator

Optic Disc Localization in Retinal Images

2013 ◽  
pp. 453-463 ◽  
Author(s):  
Florin Rotaru ◽  
Silviu Ioan Bejinariu ◽  
Cristina Diana Niţă ◽  
Mihaela Costin
Keyword(s):  
Optic Disc ◽  
Retinal Images ◽  
Optic Disc Localization

scholarly journals Localization and segmentation of optic disc in retinal images using Circular Hough transform and Grow Cut algorithm

PeerJ ◽  
2016 ◽  
Vol 4 ◽  
pp. e2003 ◽  
Author(s):  
Muhammad Abdullah ◽  
Muhammad Moazam Fraz ◽  
Sarah A. Barman
Keyword(s):  
Optic Disc ◽  
Hough Transform ◽  
Retinal Image ◽  
Diagnostic System ◽  
Retinal Images ◽  
Computer Assisted ◽  
Morphological Operations ◽  
Circular Hough Transform ◽  
Disc Center ◽  
Unique Method

Automated retinal image analysis has been emerging as an important diagnostic tool for early detection of eye-related diseases such as glaucoma and diabetic retinopathy. In this paper, we have presented a robust methodology for optic disc detection and boundary segmentation, which can be seen as the preliminary step in the development of a computer-assisted diagnostic system for glaucoma in retinal images. The proposed method is based on morphological operations, the Circular Hough transform and the Grow Cut algorithm. The morphological operators are used to enhance the optic disc and remove the retinal vasculature and other pathologies. The optic disc center is approximated using the Circular Hough transform, and the Grow Cut algorithm is employed to precisely segment the optic disc boundary. The method is quantitatively evaluated on five publicly available retinal image databases DRIVE, DIARETDB1, CHASE_DB1, DRIONS-DB, Messidor and one local Shifa Hospital Database. The method achieves an optic disc detection success rate of 100% for these databases with the exception of 99.09% and 99.25% for the DRIONS-DB, Messidor, and ONHSD databases, respectively. The optic disc boundary detection achieved an average spatial overlap of 78.6%, 85.12%, 83.23%, 85.1%, 87.93%, 80.1%, and 86.1%, respectively, for these databases. This unique method has shown significant improvement over existing methods in terms of detection and boundary extraction of the optic disc.

Automatic Localization of the Optic Disc Center in Retinal Images based on Angle Detection in Curvature Scale Space

2015 ◽  
Vol 13 (2) ◽  
pp. 1-13 ◽  
Author(s):  
A. Elbalaoui ◽  
Mohamed Fakir ◽  
M. Boutaounte ◽  
A. Merbouha
Keyword(s):  
Diabetic Retinopathy ◽  
Optic Disc ◽  
Retinal Image ◽  
Scale Space ◽  
Second Step ◽  
Retinal Images ◽  
Anatomical Structures ◽  
Disc Center ◽  
Curvature Scale Space ◽  
Automatic Localization

Digital images of the retina is widely used for screening of patients suffering from sight threatening diseases such as Diabetic retinopathy and Glaucoma. The localization of the Optic Disc (OD) center is the first and necessary step identification and segmentation of anatomical structures and in pathological retinal images. From the center of the optic disc spreads the major blood vessels of the retina. Therefore, by considering the high number of vessels and the high number of the angles resulted from the vessels crossing, the authors propose a new method based on the number of angles in the vicinity of optic disc for localization of the center of optic disc. The first step is pre-processing of retinal image for separate the fundus from its background and increase the contrast between contours. In the second step, the authors use the Curvature Scale Space (CSS) for angle detection. In the next step, they move a window about the size of optic disc to count the number of corners. In the final step, they use the center of windows which has the most number of corners for localizing the optic disc center. The proposed method is evaluated on DRIVE, CHASE_DB1 and STARE databases and the success rate is 100, 100 and 96.3%, respectively.

Localization of the optic disc center in retinal images based on the Harris corner detector

2012 ◽  
Vol 2 (3) ◽  
pp. 198-206 ◽  
Author(s):  
Amin Dehghani ◽  
Mohammad-Shahram Moin ◽  
Mohammad Saghafi
Keyword(s):  
Optic Disc ◽  
Retinal Images ◽  
Disc Center ◽  
Harris Corner ◽  
Harris Corner Detector

New Simplified Fovea and Optic Disc Localization Method for Retinal Images

2019 ◽  
Vol 9 (4) ◽  
pp. 847-855 ◽  
Author(s):  
Shaohua Zheng ◽  
Youxing Zhu ◽  
Lin Pan ◽  
Ting Zhou
Keyword(s):  
Optic Disc ◽  
Retinal Images ◽  
Localization Method ◽  
Optic Disc Localization
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