Simulation and Synthesis in Medical Imaging
Can Zhao, Jelmer M. Wolterink, David Svoboda, Ninon Burgos
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The 16 full papers presented were carefully reviewed and selected from 21 submissions. The contributions span the following broad categories in alignment with the initial call-for-papers: methods based on generative models or adversarial learning for MRI/CT/PET/microscopy image synthesis, image super resolution, and several applications of image synthesis and simulation for data augmentation, segmentation or lesion detection.