This project detects breast cancer from histopathology images using a Convolutional Neural Network (CNN). The system analyzes tissue images to classify them as normal or cancerous.
- Patch Creation: Large histopathology images are divided into smaller sections called patches. This allows the CNN to focus on detailed tissue patterns, improving accuracy and training efficiency.
- Image Preprocessing: Patches are resized and normalized for consistent input to the model.
- CNN Model: Learns features from patches to classify tissue as normal or cancerous.
- Model Saving: The trained model is saved in
.kerasformats for future predictions.
- Login Page
- Dashboard Page for image upload and prediction
- Programming: Python
- Libraries: TensorFlow, Keras, OpenCV, NumPy, PIL
- Web: Flask, react-vite
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