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Early Detection of Glaucoma Disease using Image Processing
Based on the survey of various Image processing techniques, for increasing the accuracy, processing speed as well as the efficiency and reliability of the system, one will be able to use an efficient technique for the Glaucoma which is a major eye disease globally. A new and comprehensive method for an efficient detection of the disease which is a combination of techniques that exits in CDR and Blood vessel calculation with the help of SLIC superpixel classification and Hue transform for the non evasive contribution to the study and research for Glaucoma Disease is proposed. The key image handling strategies incorporate image enlistment, image combination, image segregation, highlight extraction, image improvement, morphology, design coordinating, image order, examination and factual estimation. These techniques are altogether computed using MATLAB software tool with the help of GUI to allow medical practitioners to determine whether a person is suffering from Glaucoma or not. Thus the Brightness Information of the optic cup can be directly used to determine and classify the said disease depending upon a specific and standardized threshold value.
Blood Vessels, Cup to Disc Ratio (CDR), Fluid Pressure, Fundus Image, Glaucoma Disease, MATLAB IP, Optic Cup (OC), Optic Disc (OD), Region of Interest(ROI), Support Vector Machine (SVM).
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