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.

Table of Contents

• Description
• Overview
• Problem Statement
• Installation
• License
• Contact Information

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.

Installation

1. Clone the repository

git clone https://github.com/dilshankarunarathne/kidney-stones-detection-system.git

2. Install the required packages

cd kidney-stones-detection-system
cd backend
pip install -r requirements.txt

cd kidney-stones-detection-system
cd frontend
npm install

3. Download the dataset and models Dataset: CT KIDNEY DATASET: Normal-Cyst-Tumor and Stone
   Run the notebooks inside the ML directory to train the models and save them.

4. Run the application

cd kidney-stones-detection-system
cd backend
uvicorn main:app --reload

cd kidney-stones-detection-system
cd frontend
npm start

Contributing

If you'd like to contribute to this project, please check the contribution guidelines for more information.

License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Contact Information

For questions or feedback, please contact the author:

• Author: Dilshan M. Karunarathne
• Email: ceo@altier.tech
• Website: http://altier.tech
• Copyright: © 2022-2024