Future trends in medical and biomedical image synthesis

The contributions of this book demonstrate a wide variety of image synthesis and simulation methods, from parametric modeling to deep learning, and their application to diverse tasks such as image enhancement or data augmentation. The ultimate goal when developing methods is to design a simulation system that can produce realistic anatomical or biological images for diverse acquisition conditions and that is fully controllable, accurate, robust, simple to use, fast and easily accessible to all. This would ideally lead to simulated/augmented data of high quality, high variability and high fidelity (both spatially and in time). However, several challenges remain. This chapter will highlight current limitations and identify possible future research directions.