SECURED's Synthetic Data Generation service relies in the SECURED's SDG library to generating synthetic medical data including mammograms, chest X-rays, CTGs, and MRIs. It aims to provide data that is statistically similar to the original data but does not convey information from the original data. This service can produce data that is similar to the original, but not completely equal to the original data to avoid data leakage. Aside from privacy, synthetic data generation can also be useful as it can be used to complement real data for tasks such as training Machine Learning models, specially Deep Learning models, which require as much data as possible to provide good and generalizable results.