We can use the RF data for deep learning model training. Our main Treget RF image to B-mode image. How can we solve this using GAN? If anyone has good code experience please share it with me.
For image reconstruction, particularly in medical imaging, GANs can be effective, with several variants such as CycleGAN, Pix2Pix, SRGAN, and WGAN-GP showing good performance for reconstruction tasks. However, newer models like Diffusion Models, Transformers for Image Generation with Diffusion, and Vision Transformers (ViT) are often better choices for achieving high-quality and stable reconstructions.
Here are some references you may find helpful:
For GANs:
Super-Resolution Image Reconstruction Based on Self-Calibrated Convolutional GAN. https://arxiv.org/pdf/2106.05545