DeepMammo
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Convolutional Neural Network and It's Application in Breast tumor Classification ...learn more
Overview / Usage
- Rectangle patches that contains the whole tumor region (plus 10% surrounding region)
is extracted from each modality and view image - All the patches are resized to the same size (224*224)
Each patient, 4 images are fed into GoogLeNet, and get 4096 features (1024
for each image) at the last layer - Random forest (RF) is implemented to select important features from all
4096 features (based on Gini impurity) - 137 features are kept and fed into another RF for final classification into
Benign (-) or Malignant (+)