The EMory BrEast imaging Dataset (EMBED): A Racially Diverse, Granular Dataset of 3.5M Screening and Diagnostic Mammograms

Understand

Developing and validating artificial intelligence models in medical imaging requires datasets that are large, granular, and diverse.

• To date, the majority of publicly available breast imaging datasets lack in one or more of these areas.
• Models trained on these data may therefore underperform on patient populations or pathologies that have not previously been encountered.
• The EMory BrEast imaging Dataset (EMBED) addresses these gaps by providing 3650,000 2D and DBT screening and diagnostic mammograms for 116,000 women divided equally between White and African American patients.