Automatic segmentation of age-related macular degeneration in retinal fundus images
Computers in Biology and Medicine
Simple and Robust Optic Disc Localisation Using Colour Decorrelated Templates
ACIVS '08 Proceedings of the 10th International Conference on Advanced Concepts for Intelligent Vision Systems
A computational-intelligence-based approach for detection of exudates in diabetic retinopathy images
IEEE Transactions on Information Technology in Biomedicine - Special section on biomedical informatics
Journal of Medical Systems
Segmentation of optic disc in retinal images using an improved gradient vector flow algorithm
Multimedia Tools and Applications
Automated optic disk localization and detection in colored retinal images
Proceedings of the 7th International Conference on Frontiers of Information Technology
Fast localization of the optic disc using projection of image features
IEEE Transactions on Image Processing
Computer Methods and Programs in Biomedicine
ICMB'10 Proceedings of the Second international conference on Medical Biometrics
Retinal images: optic disk localization and detection
ICIAR'10 Proceedings of the 7th international conference on Image Analysis and Recognition - Volume Part II
A composite architecture for an automatic detection of optic disc in retinal imaging
SITE'12 Proceedings of the 11th international conference on Telecommunications and Informatics, Proceedings of the 11th international conference on Signal Processing
Computer Methods and Programs in Biomedicine
Detecting optic disc on asians by multiscale gaussian filtering
Journal of Biomedical Imaging - Special issue on Advances in Computer-Aided Detection and Diagnosis
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The location of the optic disc is of critical importance in retinal image analysis. In this work we improve on an approach introduced in [3] which localises an optic disc region through greylevel morphology followed by snake fitting. We propose and implement both the automaticinitialisation of the snake and the application of morphology in colour space. We examine various methods of performing the morphology step (to remove the interference of blood vessels) and compare them against each other. We demonstrate that our proposed simple Lab colour morphology method is particularly suitable for the characteristics of our optic disc images. Results indicate 90.32% average accuracy in localising the optic disc boundary.