I have a dataset including paired MRI and CT of patients. My aim is generating synthetic CT from MRI images. As I have paired images, which GAN network is the best for this purpose? CycleGAN OR pix2pix? Which one result in a synthetic CT with a higher quality? Can I use CycleGAN to feed the model with paired images in an unpaired manner? Does CycleGAN has any advantages over the pix2pix for my purpose?
Any advice would be highly appreciated
We both don't know that. But you can make conditional CycleGAN to control paired images. In my case, the dataset decided the quality of image by reduce the number of bad samples. Both pix2pix and CycleGAN can work well. If you focused on higher resolution (sharper but noisier), you can choose ResNet as Generator. If your task was segmentation, I think U-Net is better to use (https://biomedical-engineering-online.biomedcentral.com/articles/10.1186/s12938-019-0682-x)