This paper presents RegL (Labels Regularizer), a methodology that includes different image pre-processes to allow both a correct breast segmentation and the enhancement of image quality through an intensity adjustment, thus allowing the use of deep learning to classify the mammograms into BI-RADS categories.  The combination of five networks implementing the RegL methodology achieved the best results among all the models in the test set. 
RegL
The Confusion Matrix (CM) - CNN network used implements an architecture that models each radiologist's noisy label. 
Confusion Matrix (CM) - CNN network