Assessing the Efficacy of StyleGAN 3 in Generating Realistic Medical Images with Limited Data Availability

Author:

Che Azemin Mohd Zulfaezal1ORCID,Mohd Tamrin Mohd Izzuddin1ORCID,Hilmi Mohd Radzi1ORCID,Mohd Kamal Khairidzan1ORCID

Affiliation:

1. International Islamic University Malaysia, Malaysia

Publisher

ACM

Reference18 articles.

1. Analysis of generative adversarial networks

2. Anonymous Gastritis Image Generation via Adversarial Learning from Gastric X-Ray Images

3. Medical Image Synthesis with Deep Convolutional Adversarial Networks

4. Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter. 2017. Gans trained by a two time-scale update rule converge to a local nash equilibrium. In Proceedings of the Advances in Neural Information Processing Systems (NIPS ‘17), December 4-9, Long Beach, California.

5. Image synthesis in contrast MRI based on super resolution reconstruction with multi-refinement cycle-consistent generative adversarial networks

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