Renal Disease Classification Using Image Processing

The growth of renal disease has increased gradually and affected millions of people and the number of affected people increases each year. Chronic kidney disease usually occurs due to abnormal albumin excretion which reduces the functioning of the kidney by more than three months. On the view of life expectancy, 7.6% of the deaths are due to chronic kidney disease and it accounted for 4.6% of all-cause mortality. And the best to treat renal diseases is early prophylaxis which is achieved by accurately diagnosing the patient at the very early stages. The diagnostic methods include ultrasonographic diagnosis which is a cheaper, more convenient, and timeliness method. This paper presents renal disease detection and classification using supervised techniques which classifies disease with up to 97 percent accuracy and uses image processing tools for kidney stone detection with an accuracy of 95%.