Breast Cancer Detection using Deep Learning

This project implements a Convolutional Neural Network (CNN) to classify breast cancer images as either benign or malignant.

Setup

1. Install dependencies:

pip install -r requirements.txt

2. Data Organization: Place your dataset in the following structure:

C:/Datasets/BreastCancer/
├── training/
│   ├── benign/
│   └── malignant/
└── testing/
    ├── benign/
    └── malignant/

3. Run the model:

python app.py

Model Architecture

• Input: Grayscale images (120x120 pixels)
• 2 Convolutional layers with MaxPooling
• Dense layers for classification
• Binary output (benign/malignant)

Performance Metrics

The model evaluates accuracy and loss on the test set.