Contributed MRI analysis with ResNet50 + PyTorch

[rakheshkrishna2005]

• Fixes: MRI Image Analysis - Deep Learning ResNet-50 (98% Train Accuracy) #695

🧠 Alzheimer’s Disease Classifier - MRI Image Analysis

📝 Description

• Alzheimer’s Disease Classifier is a computer vision application that uses a ResNet-50 model to classify MRI images for Alzheimer's stages.
• Built with Streamlit for a user-friendly web interface, the app can classify multiple uploaded MRI images at once.
• Provides insights and treatment recommendations based on classification.

🎥 Demo Video

Screen.Recording.2024-10-31.154940.mp4

🚀 Features

• 🖼️ Multiple Image Upload with uploaded images info
• 📊 Detailed classification report for each image
• 🔍 Four-class classification for Alzheimer's stages
• 💡 Comprehensive treatment recommendations for each stage

💻 Tech Stack

• Programming Language: Python 🐍
• Web Framework: Streamlit 🌐
• Deep Learning Framework: PyTorch 🔥
• Leveraged Pre-trained Model: ResNet-50 🦾

⚙️ Installation and Usage

Follow these steps to get the Alzheimer's Disease Classifier running on your machine:

1. Clone the repository:

   git clone https://github.com/UppuluriKalyani/ML-Nexus.git

2. Navigate to the Project Directory:

   cd ML-Nexus/Neural Networks/Alzheimer MRI Analysis

3. Create a virtual environment (optional but recommended):

   python -m venv venv

4. Activate the Virtual Environment:

   • On Windows:

     venv\Scripts\activate

   • On macOS/Linux:

     source venv/bin/activate

5. Install the required dependencies:

   pip install -r requirements.txt

6. Run the Streamlit app:

   streamlit run app.py

7. Access the app by opening your web browser and navigating to http://localhost:8501.

🌐 Web Interface

📚 Additional Resources

• 📘 PyTorch Documentation
• 📘 Streamlit Documentation
• 📘 ResNet-50 Documentation

[github-actions]

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[github-actions]

🎉🎉 Thank you for your contribution! Your PR #698 has been merged! 🎉🎉