Glaucoma and Diabetic Retinopathy Diagnosis using Image Mining

Abstract

In today's world human are affected by various diseases which lead to damage of some or the other body part which degrades their working speed. Eye diseases are one of the factors, which include vision loss due to glaucoma and diabetic retinopathy. Glaucoma damages the optic nerve of the eye. DR cause changes in eye damage the blood vessel. Image will undergo a standard method of applying image processing which include image acquisition, pre-processing, feature extraction followed by exact identification of disease by means of a classifier. Various classifiers are available in data mining that have been used for classification in different areas. We will use SVM for classification of the retinal images into category of Normal, DR and Glaucoma. The Overall classification rate of the proposed system will give the better efficiency and accuracy of identifying the disease with respect to existing systems.

Design and Implementation System to Measure the Impact of Diabetic Retinopathy Using Data Mining Techniques

“…The hemorrhages, on the other hand, look similar to microaneurysm, but they are located in the deeper layers of the retina with unorganized shapes and sizes [2].The various ways of medical images can be classified based on the following criteria: texture, neural networks, and data mining task. The types obtained from the last criterion are considered the best among all other types because they help improve the accuracy of the classification [3].A large amount of data extracted from the retinal images is provided to a database while the proposed algorithm helps discover how new images are classified according to the useful information stored in the database. The increase number of diabetic patients in health care systems indicates an increase in the data as well.…”