Brain Tumor Detection and Segmentation Web Application
Overview
This project is a web-based application that utilizes deep learning models to classify and segment brain tumors from MRI images. The application is built to assist in the early detection and analysis of brain tumors, providing crucial information for diagnosis and treatment planning.
Features
- Image Classification: The app predicts the type of brain tumor (glioma, meningioma, pituitary, or no tumor) from the uploaded MRI image.
- Tumor Segmentation: The app segments the brain tumor in the MRI image, providing a mask that highlights the tumor region.
- Probability Score: The app displays the confidence level of the classification model's prediction.
Technologies Used
Backend:
- Python
- Flask (Web framework)
- TensorFlow (for segmentation model)
- PyTorch (for classification model)
Frontend:
- HTML/CSS (Web page structure and styling)
- JavaScript (Client-side interactivity)
- Bootstrap (Responsive design framework)
Other Tools:
- OpenCV (Image processing)
- Matplotlib (Visualization)
- PIL (Python Imaging Library)
WebApp
