Synthetic CT Imaging Using Limited Patch-Based Cyclegan for Adaptive Radiotherapy
Cycle generative adversarial network (GAN) has a difficulty in maintaining the structural integrity in a synthesized image for complex organs and tissues. In this study, we proposed a CycleGAN including multi-scale blocks and attention gates for improving the...
Poster Program · Therapy Physics
CT Image Denoising Using Patch-Based Reinforcement Learning with Frequency-Selective Actions
The patch-based network training is widely used for CT denoising due to computation memory and time constraints. However, conventional techniques are limited to learncontextual information and preserve fine structures. In this study, we proposed a patch-based...
Poster Program · Diagnostic and Interventional Radiology Physics
