  This work focuses on the automatic quantification of the breast density from
digital mammography imaging. Using only categorical image-wise labels we train
a model capable of predicting continuous density percentage as well as
providing a pixel wise support frit for the dense region. In particular we
propose a weakly supervised loss linking the density percentage to the mask
size.
