Kidney Stone Detection using Fuzzy C-means Clustering

Abstract

This project aims to create a computer-aided detection system using MATLAB to help healthcare professionals detect kidney stones. Image processing techniques are used to analyse ultrasound images of the kidneys. The main goal of our work is to use deep semantic segmentation learning models trained using the proposed approach to provide precise and accurate segmentation results. The algorithm detects the presence of stones by analysing the size, shape, and density of the structures in the images. The system can be configured to optimize the detection parameters based on the type of stone being analysed. By automating the detection process, the system reduces the possibility of human error while improving the accuracy and consistency of the diagnosis. The proposed system can also give us the size of the stone. The proposed system has the potential to be a valuable tool for healthcare professionals in the early detection of kidney stones.