A Model-Based Approach for Automated Feature Extraction in Fundus Images
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Digital Image Processing (3rd Edition)
Digital Image Processing (3rd Edition)
Retinal images: optic disk localization and detection
ICIAR'10 Proceedings of the 7th international conference on Image Analysis and Recognition - Volume Part II
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Digital fundus imaging is used to diagnose various eye diseases like diabetic retinopathy, diabetic maculopathy and age related macular degeneration. Macula is the main central part of retina which is responsible for sharp vision and any changes in macula cause severe effects on vision. In this paper, we propose a novel method for automated detection of macula from digital fundus images. The proposed system performs preprocessing, optic disc detection and blood vessel segmentation prior to macula detection. In macula detection, it formulates a feature vector and uses Gaussian Mixture Model for detection of macular region. We evaluate the proposed technique using publicly available fundus image database MESSIDOR. The results show the validity of proposed system and are found to be competitive with previous results in the literature.