Unsupervised Medical Image Translation Using Cycle-MedGAN

Understand

Image-to-image translation is a new field in computer vision with multiple potential applications in the medical domain.

• However, for supervised image translation frameworks, co-registered datasets, paired in a pixel-wise sense, are required.
• This is often difficult to acquire in realistic medical scenarios.
• On the other hand, unsupervised translation frameworks often result in blurred translated images with unrealistic details.