An Improved Deep Learning Framework for MR-to-CT Image Synthesis with a New Hybrid Objective Function
Author:
Affiliation:
1. University of Wollongong,Australia
2. University of New South Wales,Australia
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9761376/9761399/09761546.pdf?arnumber=9761546
Reference23 articles.
1. Unsupervised MR-to-CT Synthesis Using Structure-Constrained CycleGAN
2. Attention-Aware Discrimination for MR-to-CT Image Translation Using Cycle-Consistent Generative Adversarial Networks
3. Unpaired Image-to-Image Translation Using Cycle-Consistent Adversarial Networks
4. Patch‐based generative adversarial neural network models for head and neck MR‐only planning
5. Comparison of Supervised and Unsupervised Deep Learning Methods for Medical Image Synthesis between Computed Tomography and Magnetic Resonance Images
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