Description

A urinary stone, or renal calculi, is one of the most frequent abnormalities in the urinary system. Each year, more than half a million people visit emergency rooms for urinary stone problems.Computer-assisted detection techniques developed to date to improve diagnosis without multiple systematic readings have not resulted in a significant improvement in performance measures. In this process, the use of automatic image processing techniques resulting from machine learning represents a detection and classification of kidney stone in medical images. As well as the performance of the process is evaluated by means of the accuracy.