Automatic Localization and Boundary Detection of Optic Disc Using Implicit Active Contours

An efficient detection of Optic disc in colour retinal images is the fundamental step in an automated retinal image analysis system. This paper presents a new approach for the automatic localization and accurate boundary detection of the optic disc. Iterative thresholding method followed by connected component analysis is employed to locate the approximate center of the optic disc. Then geometric model based implicit active contour model is applied to find the exact boundary of the optic disc. The method is evaluated against a carefully selected database of 148 retinal images and compared with the human expert. The optic disc is localized with an accuracy of 99.3%. The sensitivity and specificity of boundary detection achieved in terms of Mean±SD are 90.67±5 and 94.06±5 respectively.

[1]  Chunming Li,et al.  Implicit Active Contours Driven by Local Binary Fitting Energy , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[2]  Majid Mirmehdi,et al.  Colour Morphology and Snakes for Optic Disc Localisation , 2002 .

[3]  B. Thomas,et al.  Automated identification of diabetic retinal exudates in digital colour images , 2003, The British journal of ophthalmology.

[4]  Demetri Terzopoulos,et al.  Snakes: Active contour models , 2004, International Journal of Computer Vision.

[5]  J. Thiran,et al.  Identification of the optic disk boundary in retinal images using active contours , 1999 .

[6]  Langis Gagnon,et al.  Procedure to detect anatomical structures in optical fundus images , 2001, SPIE Medical Imaging.

[7]  Marco Furini,et al.  International Journal of Computer and Applications , 2010 .

[8]  Pascale Massin,et al.  A contribution of image processing to the diagnosis of diabetic retinopathy-detection of exudates in color fundus images of the human retina , 2002, IEEE Transactions on Medical Imaging.

[9]  C. Sinthanayothin,et al.  Automated localisation of the optic disc, fovea, and retinal blood vessels from digital colour fundus images , 1999, The British journal of ophthalmology.

[10]  Huiqi Li,et al.  Automated feature extraction in color retinal images by a model based approach , 2004, IEEE Transactions on Biomedical Engineering.

[11]  P.C. Siddalingaswamy,et al.  Automated Detection of Anatomical Structures in Retinal Images , 2007, International Conference on Computational Intelligence and Multimedia Applications (ICCIMA 2007).

[12]  Ecosse L Lamoureux,et al.  Assessment of optic disc cupping with digital fundus photographs. , 2005, American journal of ophthalmology.

[13]  Shankar M. Krishnan,et al.  Automatic image analysis of fundus photograph , 1997, Proceedings of the 19th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. 'Magnificent Milestones and Emerging Opportunities in Medical Engineering' (Cat. No.97CH36136).