An Automated System To Identify Wilson Disease By KNN Based On Sift Features P.Suganya,et al,

Wilson disease is a pathology because of a gene mutation causing malfunction in the copper excretion from the organism. Therefore, copper accumulation in the human body gives rise to oxidative processes. Hence, Wilson disease causes several disorders including affecting tissues and organs. Neurological disorders leads to copper accumulation in the human body. Approximately 95% of individuals with neurological/psychiatric disorders shows a visible symptom in their eye known as Kayser-Fleischer ring. The characteristic sign of KF ring will be golden-brown or greyish in color, it occurs due to the copper deposition in the cornea. In the medical screening, it is consider as a diagnostic sign of Wilson disease. Our system proposed an innovative technique based on ocular biometric measurements to diagnose the disease . An image processing algorithm will detects the Kayser-Fleischer ring in the cornea through segmentation process. Biometric measurements provides further information on the severity level of Wilson disease. Also, an image processing algorithm is proposed to provide an invasive technique which is used to improve the accuracy of the severity measurements. As input image is performed using SIFT feature extraction. Finally the images will be classified as normal or affected using KNN classifier and Decision tree.