Mini - Project (M. Eng)

Development of a deep learning model for automated detection of Breast Cancer 💻

This project is on a mission to save lives! 💪 Our goal is to develop a deep learning solution for the classification of breast cancer using histopathological images. We want to investigate the best possible outcome using the VGG-16 architecture and normalization techniques such as image tilting, zooming, and rotation. The focus is to improve the accuracy and reliability of breast cancer diagnosis through the integration of computer vision and image processing techniques.

1. Implement a deep learning model using the VGG-16 architecture for the classification of breast cancer.
2. Evaluate the model's performance using various normalization techniques.
3. Improve the accuracy and reliability of breast cancer diagnosis through the integration of computer vision and image processing techniques.

• Python 3.x
• Tensorflow
• Keras
• OpenCV
• Numpy
• Matplotlib

1. Clone the repository

git clone https://github.com/[username]/[repository].git

2. Install the required libraries

pip install -r requirements.txt

3. Run the Jupyter Notebook file breast_cancer_detection.ipynb

This project serves as a proof-of-concept for the potential of deep learning in automating the detection of breast cancer. The model developed in this project can serve as a starting point for further improvement and optimization towards creating a robust and accurate tool for the diagnosis of breast cancer. Let's change the world, one deep learning model at a time! 🚀

Note: This description is based on information available as of 2021-22 and may not reflect the current state of the project.