In Japan, the assessment of breast density during mammography screening is still practiced, partly due to challenges in achieving objective evaluations of density.
A deep learning algorithm was developed to automatically determine breast density from mammography images, processing them into standardized grayscale and calculating relative density based on fatty tissue.
The system successfully calculated breast density from almost all images, achieving a correlation of 76.6% with human evaluations, highlighting its potential to enhance mammography screening efficiency.