Optic Disc Segmentation in Retinal Fundus Images Using Morphological Techniques and Intensity Thresholding

Among the many diseases that affect the retina, there are two serious diseases: Diabetic Retinopathy and Glaucoma. Diabetic Retinopathy (DR) is a sight-threatening risk inflicting disorder diabetic patient. It occurs due to damage in the retina as a result of diabetes. Glaucoma is a disease of the retinal system that damages the optic nerve of the eye and gets worse over time. A buildup of pressure inside the eye is often associated with it, so it can damage the optic nerve that transmits images to the brain. If damage to the optic nerve caused by high eye pressure continues, glaucoma causes permanent vision loss. Early diagnosis and treatment have been shown to prevent blindness and visual loss. Compared with the manual diagnostic methods, automated retinal analysis systems help save patients’ time, cost and vision. In this context, a fundamental process for diagnosing these diseases is the precise and effective localization of the Optic Disc (OD) in retinal images. This paper offers a robust and efficient method for automatic diagnosis of OD. The method starts with removing the undesirable portions of the image, such as noise, reflections and blur. Next, the OD has been detected by means of morphological operations considering the intensity threshold feature. The proposed method is fast and robustness to detect OD even if interrupted by the visible blood vessels. This method was applied on seven data sets which are the Origa, Rim-One 3, Drishti, Messidor, Drions, Diaretdb0 and DIARETDBI, and the resulted accuracy for these data set are 98.46, 97.48, 97.03, 98.75, 97.27, 95.38, 95.45 respectively.

[1]  Hossein Rabbani,et al.  A dictionary learning based method for detection of diabetic retinopathy in color fundus images , 2017, 2017 10th Iranian Conference on Machine Vision and Image Processing (MVIP).

[2]  Arwa Ahmed,et al.  Optic Disc Segmentation Using Manual Thresholding Technique , 2019 .

[3]  Kaamran Raahemifar,et al.  Optic disc segmentation for glaucoma screening system using fundus images , 2017, Clinical ophthalmology.

[4]  Baidaa Al-Bander,et al.  Multiscale sequential convolutional neural networks for simultaneous detection of fovea and optic disc , 2018, Biomed. Signal Process. Control..

[5]  Muhammad Moazam Fraz,et al.  Fast Optic Disc Segmentation in Retina Using Polar Transform , 2017, IEEE Access.

[6]  Chengdong Wu,et al.  Automatic Optic Disc Segmentation Based on Modified Local Image Fitting Model with Shape Prior Information , 2019, Journal of healthcare engineering.

[8]  Safak Bayir,et al.  Automatic Detection of Optic Disc in Retinal Image by Using Keypoint Detection, Texture Analysis, and Visual Dictionary Techniques , 2016, Comput. Math. Methods Medicine.

[9]  Xun Xu,et al.  Deep multiple instance learning for automatic detection of diabetic retinopathy in retinal images , 2017, IET Image Process..

[10]  Hanung Adi Nugroho,et al.  Optic Disc Segmentation Based on Red Channel Retinal Fundus Images , 2015, SOCO 2015.

[11]  Hanung Adi Nugroho,et al.  Segmentation of optic disc and optic cup in colour fundus images based on morphological reconstruction , 2017, 2017 9th International Conference on Information Technology and Electrical Engineering (ICITEE).

[12]  Junaidi Abdullah,et al.  Fast optic disc segmentation using FFT-based template-matching and region-growing techniques , 2018, Comput. methods Biomech. Biomed. Eng. Imaging Vis..

[13]  Agus Harjoko,et al.  Optic disc and cup segmentation by automatic thresholding with morphological operation for glaucoma evaluation , 2017, Signal Image Video Process..

[14]  Taimur Hassan,et al.  Fully Automated Robust System to Detect Retinal Edema, Central Serous Chorioretinopathy, and Age Related Macular Degeneration from Optical Coherence Tomography Images , 2017, BioMed research international.

[15]  Anushikha Singh,et al.  Blood vessel inpainting based technique for efficient localization and segmentation of optic disc in digital fundus images , 2016, Biomed. Signal Process. Control..

[16]  Sumantra Dutta Roy,et al.  Optic Disc Segmentation in Fundus Images Using Anatomical Atlases with Nonrigid Registration , 2018, Communications in Computer and Information Science.

[17]  Soumyadeep Pal,et al.  Mathematical morphology aided optic disk segmentation from retinal images , 2017, 2017 3rd International Conference on Condition Assessment Techniques in Electrical Systems (CATCON).

[18]  Ganesh R. Naik,et al.  Retinal Fundus Image Analysis for Diagnosis of Glaucoma: A Comprehensive Survey , 2016, IEEE Access.