Breast-Cancer-Detection-from-Ultrasound-pictures-using-CNN

CNN to classify ultrasounds of cancerous and non cancerous cells

Topic

Topic In this notebook I will be dealing with ultrasound pictures classification. The task is to be able to tell from scan pictures whether a tumor is benign or cancerous. I will be using a convolutional network to classify the images and will try to achieve an accuracy above 80%.

Objective

• Detect the existance of breast cancer from ultrasound images

Summary

• Importing Libraries
• The Dataset
• Creating the transforms and data loaders
• Some Dataviz
• Creating the classifier
• Training and validation
• Testing the model
• Evaluation metrics
• Trying out the model
• Conclusion

Libraries

• Pandas
• Numpy
• Sklearn
• Torch vision
• CV2
• Glob

Evaluation metrics

• Confusion matrix
• Classification report
• Accuracy

Data source

https://www.kaggle.com/datasets/vuppalaadithyasairam/ultrasound-breast-images-for-breast-cancer?fbclid=IwAR20PikUw-IiuE0hNEi3i_h79qaTtSfmqq-nJhVh_9L1op_DSO8BXuRfMpI