Colormedgan: a semantic colorization framework for medical images

HIGHLIGHTS

• who: Shaobo Chen and colleagues from the College of Information Science and Technology, Jinan University, Guangzhou, China have published the research work: ColorMedGAN: A Semantic Colorization Framework for Medical Images, in the Journal: (JOURNAL)
• what: To address the texture detail of and the scarcity of paired data the authors propose self-supervised colorization framework based on CycleGAN(Cycle-Consistent Generative Adversarial Networks) treating the colorization problem of as cross-modal domain transfer problem in color space. The experiments demonstrate that current models cannot generate high-quality colorized medical images. Drawing inspiration from these works, the . . .
  

   

  

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