Simultaneous Dual-View Mammogram Synthesis Using Denoising Diffusion Probabilistic Models

ArXi:2604.05110v1 Announce Type: cross Breast cancer screening relies heavily on mammography, where the craniocaudal (CC) and mediolateral oblique (MLO) views provide complementary information for diagnosis. However, many datasets lack complete paired views, limiting the development of algorithms that depend on cross-view consistency. To address this gap, we propose a three-channel denoising diffusion probabilistic model capable of simultaneously generating CC and MLO views of a single breast.