The Brain-Tumor-QCNN-ResNet project implements a hybrid Quantum-Classical model for classifying brain tumors. This software uses advanced techniques like Quantum FiLM modulation and the ResNet-18 architecture. It efficiently detects multiple types of MRI tumors, helping improve diagnosis and patient care in healthcare settings.
To get started with the Brain-Tumor-QCNN-ResNet application, follow these simple instructions.
Before you install the application, ensure that your system meets the following requirements:
- Operating System: Windows 10 or later, macOS Mojave or later, or Ubuntu 18.04 or later.
- Memory: At least 8 GB of RAM.
- Storage: Minimum 1 GB of free disk space.
- Software Dependencies:
- Python 3.6 or later
- PyTorch
- PennyLane
-
Visit the Releases Page
Go to the releases page to find the latest version of the software:
Download Here -
Select the Desired Version
Once on the releases page, locate the version you want to download. The latest version is generally at the top of the list. -
Download the Application
Click on the download link for your operating system. The file will download automatically. Make sure to note where the file is saved on your computer. -
Run the Installer
Navigate to the downloaded file. Double-click the installer to begin the installation process. Follow the prompts to complete the installation. -
Start the Application
After installation, find the application in your Applications folder or Start Menu. Click to open it and begin using the software.
-
Load MRI Images
Use the designated area within the app to upload your MRI images for analysis. -
Select the Detection Mode
Choose from various tumor detection modes based on clinical requirements. Each mode is tailored for specific cases. -
Run the Analysis
Press the "Analyze" button to start the detection process. The application will process the data using its advanced models. -
View Results
The results will appear on your screen, detailing the type of tumor and confidence levels. You can export the results for further review or documentation.
If you encounter any issues during installation or use, consider the following:
- Check System Requirements: Ensure your system meets all prerequisites listed earlier.
- Update Software: Verify that Python and all dependencies are up to date.
- Refer to Log Files: The application generates log files that can provide insights into any errors. Check these for troubleshooting.
You are not alone. For additional help, visit our community forum or issue tracker on GitHub, where users and developers share solutions and answer questions.
The Brain-Tumor-QCNN-ResNet application operates under a community-friendly license. Please respect the licensing terms when using or modifying the software.
For those who want to explore the technology behind the application, we provide detailed documentation on the following topics:
- AI in Medicine: Explore how AI transforms healthcare and diagnostic processes.
- Deep Learning Frameworks: Understand the basics of PyTorch and its role in machine learning.
- Quantum Computing in Healthcare: Learn about how quantum techniques can elevate diagnostic accuracy.
We thank the contributors and researchers who have supported the development of the Brain-Tumor-QCNN-ResNet project. Their dedication provides the foundation for better healthcare solutions.
For direct inquiries or feedback, please feel free to reach out via issues or discussions on our GitHub repository. Your input helps us improve the application.