It is the computational processing of images that reveals the finest details of a sample placed under all kinds of different light microscopes. Even though this processing has come a long way, there is still room for increasing for example image contrast and resolution. Based on a unique deep learning architecture, a new computational model developed by researchers from the Center for Advanced Systems Understanding (CASUS) at HZDR and the Max Delbrück Center for Molecular Medicine is faster than traditional models while matching or even surpassing their images’ quality. The model, called Multi-Stage Residual-BCR Net (m-rBCR), was specifically developed for microscopy images.