https://github.com/sachintha-samarathunga/kidney-stones-detection-system

The "kidney-stones-Detector" is an advanced system delivering precise detection and classification of kidney conditions including stones, cysts, tumors, and normal states from medical imaging data. With an impressive accuracy of 98.87%, this machine learning-powered models offer reliable insights for medical professionals.
https://github.com/sachintha-samarathunga/kidney-stones-detection-system

cnn-classification image-processing keras machine-learning meterial-ui metplotlib opencv python reactjs tensorflow uvicorn

Last synced: 7 months ago
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The "kidney-stones-Detector" is an advanced system delivering precise detection and classification of kidney conditions including stones, cysts, tumors, and normal states from medical imaging data. With an impressive accuracy of 98.87%, this machine learning-powered models offer reliable insights for medical professionals.

• Host: GitHub
• URL: https://github.com/sachintha-samarathunga/kidney-stones-detection-system
• Owner: Sachintha-Samarathunga
• License: mit
• Created: 2024-02-04T18:21:03.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2025-02-11T10:00:16.000Z (9 months ago)
• Last Synced: 2025-02-11T11:22:03.517Z (9 months ago)
• Topics: cnn-classification, image-processing, keras, machine-learning, meterial-ui, metplotlib, opencv, python, reactjs, tensorflow, uvicorn
• Language: Jupyter Notebook
• Homepage:
• Size: 1.44 MB
• Stars: 3
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# Final Year Research & Project

## Kidney Stones Detection System Through AI-Enhanced Image Processing

The main objective of this project is to detect the kidney stone from the digital ultrasound image of 

the kidney by performing various image processing techniques. By utilizing advanced machine learning 

algorithms and image processing techniques.

front-end - https://github.com/Sachintha-Samarathunga/Kidney-Stones-Detector-front-end.git

[![Version](https://img.shields.io/badge/version-1.0-brightgreen.svg)](https://pypi.org/project/ad-topic-recommender/)

[![License](https://img.shields.io/badge/license-CC%20BY--NC--SA%204.0-blue.svg)](https://creativecommons.org/licenses/by-nc-sa/4.0/)

![01](https://github.com/Sachintha-Samarathunga/Kidney-Stones-Detection-System/assets/98406068/debafffe-ac9a-49d1-b9db-a82963c4048b)

![02](https://github.com/Sachintha-Samarathunga/Kidney-Stones-Detection-System/assets/98406068/83558819-05a1-416e-adf9-0c2c154c70ae)

![03](https://github.com/Sachintha-Samarathunga/Kidney-Stones-Detection-System/assets/98406068/9fbed485-225f-4826-aa82-0e5a3974a33d)

![04](https://github.com/Sachintha-Samarathunga/Kidney-Stones-Detection-System/assets/98406068/45941fca-fbce-4cdb-9e25-df90d9f56a75)

## Description

This is a template repository for a FastAPI back-end project. It is intended to be used as a starting 

point for a new project. It has OAuth2 authentication and JWT token generation. It also has a basic 

user model and CRUD operations for users.

## Overview

Kidney stones can be painful and dangerous if not detected early. This project aims to make the detection 

process faster and more accurate by using the power of artificial intelligence. In this project focus to 

using advanced image processing techniques and machine learning algorithms to analyze ultrasound images 

of the kidneys and identify any potential stones. It's a smart way of using computer technology to spot 

kidney stones in pictures of the kidneys, helping doctors identify and treat them faster and more accurately.

## Problem Statement

The primary goal of this project is to develop an automated system that can accurately detect the presence 

of kidney stones in ultrasound medical images.

## Contact Information

For questions or feedback, please contact the author:

- Author: Sachintha Samarathunga

- Email: sachinthasamarathunga@gmail.com