Automated Optic Disc Localization and Contour Detection Using Ellipse Fitting and Wavelet Transform

Optic disc detection is important in the computer-aided analysis of retinal images. It is crucial for the precise identification of the macula to enable successful grading of macular pathology such as diabetic maculopathy. However, the extreme variation of intensity features within the optic disc and intensity variations close to the optic disc boundary presents a major obstacle in automated optic disc detection. The presence of blood vessels, crescents and peripapillary chorioretinal atrophy seen in myopic patients also increase the complexity of detection. Existing techniques have not addressed these difficult cases, and are neither adaptable nor sufficiently sensitive and specific for real-life application. This work presents a novel algorithm to detect the optic disc based on wavelet processing and ellipse fitting. We first employ Daubechies wavelet transform to approximate the optic disc region. Next, an abstract representation of the optic disc is obtained using an intensity-based template. This yields robust results in cases where the optic disc intensity is highly non-homogenous. Ellipse fitting algorithm is then utilized to detect the optic disc contour from this abstract representation. Additional wavelet processing is performed on the more complex cases to improve the contour detection rate. Experiments on 279 consecutive retinal images of diabetic patients indicate that this approach is able to achieve an accuracy of 94% for optic disc detection.

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

[2]  Andrew W. Fitzgibbon,et al.  Direct Least Square Fitting of Ellipses , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[3]  Hamilton Am,et al.  Management of Diabetic Retinopathy , 1996 .

[4]  Mong-Li Lee,et al.  The role of domain knowledge in the detection of retinal hard exudates , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[5]  Nixon,et al.  A New Hough Transform Mapping for Ellipse Detection , 1995 .

[6]  L. Cohen,et al.  Multi-resolution algorithms for active contour models , 1996 .

[7]  J Reimer Wolter.  Manual and Color Atlas of the Ocular Fundus , 1970 .

[8]  Jerry L. Prince,et al.  Generalized gradient vector flow external forces for active contours , 1998, Signal Process..

[9]  Junaed Sattar.  Snakes , Shapes and Gradient Vector Flow , 2022 .

[10]  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.

[11]  Huiqi Li,et al.  Automatic location of optic disk in retinal images , 2001, Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205).

[12]  R. Reilly,et al.  Extraction of the optic disk boundary in digital fundus images , 1999, Proceedings of the First Joint BMES/EMBS Conference. 1999 IEEE Engineering in Medicine and Biology 21st Annual Conference and the 1999 Annual Fall Meeting of the Biomedical Engineering Society (Cat. N.

[13]  Langis Gagnon,et al.  Fast and robust optic disc detection using pyramidal decomposition and Hausdorff-based template matching , 2001, IEEE Transactions on Medical Imaging.

[14]  Mong-Li Lee,et al.  An effective approach to detect lesions in color retinal images , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[15]  Adrian S. Lewis,et al.  Image compression using the 2-D wavelet transform , 1992, IEEE Trans. Image Process..

[16]  A. Yezzi,et al.  On the relationship between parametric and geometric active contours , 2000, Conference Record of the Thirty-Fourth Asilomar Conference on Signals, Systems and Computers (Cat. No.00CH37154).

[17]  A Béchetoille,et al.  [Correlation between neuroretinal rim and optic disc areas in normal melanoderm and glaucoma patients]. , 2000, Journal francais d'ophtalmologie.

[18]  K. Yogesan,et al.  Software for 3-D visualization/analysis of optic-disc images , 1999, IEEE Engineering in Medicine and Biology Magazine.

[19]  Thomas S. Huang,et al.  Image processing , 1971 .

[20]  Tim Morris,et al.  Identifying the neuroretinal rim boundary using dynamic contours , 1999, Image Vis. Comput..

[21]  Yongmin Kim,et al.  Active contour model with gradient directional information: directional snake , 2001, IEEE Trans. Circuits Syst. Video Technol..

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

[23]  L. Bonomi,et al.  Glaucoma : concepts in evolution : morphometric and functional parameters in the diagnosis and management of glaucoma : proceedings of the symposium held in Verona, Italy, June 16, 1991 , 1991 .

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