International Journal of Technology Enhancements and Emerging Engineering Research (ISSN 2347-4289)

IJTEEE >> Volume 3 - Issue 12, December 2015 Edition

International Journal of Technology Enhancements and Emerging Engineering Research  
International Journal of Technology Enhancements and Emerging Engineering Research

Website: http://www.ijteee.org

ISSN 2347-4289

Automated Glaucoma Detection Techniques Using Fundus Image

[Full Text]



Rohan Appasaheb Borgalli, Hari Pratap Gautam , Winner George Parayil



Keywords : Intra ocular pressure, Ocular Computing Tomography, Heidelberg Retinal Tomography, Cup to Disk Ratio, Support Vector System, Artificial Neural Network.



ABSTRACT: This paper presents automated glaucoma detection techniques based on neural network and Adaptive Neuro fuzzy Inference system (ANFIS) Classifier. Digital image processing techniques, such as preprocessing, morphological operations and thresholding, are widely used for the automatic detection of optic disc, blood vessels and computation of the features of fundus image. Glaucoma is a disease of the optic nerve caused by the increase in the intraocular pressure of the eye. Glaucoma mainly affects the optic disc by increasing the cup size. It can lead to the blindness if it is not detected and treated in proper time. The detection of glaucoma through Optical Coherence Tomography (OCT) and Heidelberg Retinal Tomography (HRT) is very expensive, this limitation is removed by this Glaucoma Diagnosis system with good performance. In addition to diagnosis of Glaucoma a Graphical user interface (GUI) is developed. This GUI is used for automatic diagnosing and displaying the diagnosis result in a more friendly user interface The results presented in this paper indicate that the features are clinically significant in the detection of glaucoma. Proposed system of this paper is able to classify the glaucoma automatically with a sensitivity and specificity of 98% and 95% respectively.



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