To overcome the nonexistence of dataset suited for learning breast healing deformations, an in-house dataset was generated using MRI data from real patients combined with a multiscale biomechanical and biochemical models to simulate post-surgical breast shape. Several clinical features that might impact breast healing deformations, including breast density, tumor region, and tumor size, were considered in the creation of the dataset that is representative of the population distributions.