부산대학교 도서관

This paper aims to determine the better technique for kidney stone detection between K-Nearest Neighbor (KNN) and Convolutional Neural Networks (CNNs). As well known, the presence of kidney stones is an important topic that deserves discussion regarding expected medical outcomes. Most of the detection measures comprise CT scans, ultrasounds, and abdominal X-rays. These measures have varying effectiveness levels, hence used in the detection to prepare patients for specific treatment options. Patients' treatment options comprise percutaneous nephrolithotomy (PCNL), extracorporeal shockwave lithotripsy (ESWL), and ureteroscopy. The different detection techniques carried out for the patients are essential to test whether the patient has small or large kidney stones. One essential technique is using conventional neural networks (CNNs) technology. In this paper kidney, stone detection will be carried out using both of K-Nearest Neighbor (KNN) and CNN's techniques. A comparison between both techniques will be carried out to figure out the better. All of the simulations are carried out using MATLAB.