Breast cancer detection model trained on DDSM dataset
This repsitory is for detecting Breast Cancer on DDSM dataset.
The Data Tweaking Jupyter is used to convert the the dataset in the form
Root directory-> Class1-> images
-> Class2-> images
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And then train(resnet18 model) on the given Images for classes i.e. Benign, Malign, Normal. The repository also contains code for image class saliency map i.e. to determine what are the input features that are used by model to classify it to a specific label.
Some are the tutorial and saved model.