Breast-cancer-classification
Breast Cancer Classification using CNN and transfer learning
IMPORTANT
Absolutely, under NO circumstance, should one ever screen patients using computer vision software trained with this code (or any home made software for that matter).
If this repository helps you in anyway, show your love ❤️ by putting a ⭐ on this project ✌️
Check out the corresponding medium blog post https://towardsdatascience.com/convolutional-neural-network-for-breast-cancer-classification-52f1213dcc9.
Data
The dataset can be downloaded from here. This is a binary classification problem. I split the data as shown-
dataset train
benign
b1.jpg
b2.jpg
//
malignant
m1.jpg
m2.jpg
// validation
benign
b1.jpg
b2.jpg
//
malignant
m1.jpg
m2.jpg
//...
Environment and tools
- Jupyter Notebook
- Numpy
- Pandas
- Scikit-image
- Matplotlib
- Scikit-learn
- Keras
Installation
pip install numpy pandas scikit-image matplotlib scikit-learn keras
jupyter notebook
Model
Results
Loss/Accuracy vs Epoch
Confusion Matrix
ROC-AUC curve
Correct/Incorrect classification samples
The model is able to reach a validation accuracy of 98.3%, precision 0.65, recall 0.95, f1 score of 0.77 and ROC-AUC as 0.692.
References
Citing
@misc{Abhinav:2019,
Author = {Abhinav Sagar},
Title = {Breast-cancer-classification},
Year = {2019},
Publisher = {GitHub},
Journal = {GitHub repository},
Howpublished = {\url{https://github.com/abhinavsagar/Breast-cancer-classification}}
}
Contacts
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