A cross-domain conditional GAN generates stereo-consistent hyperrealistic endoscopic images from phantoms, showing better depth perception and realism than baseline image-to-image methods in evaluations by 6 raters.
Flex- ible and Comprehensive Patient-Specific Mitral Valve Silicone Models with Chor- dae Tendinae Made From 3D-Printable Molds
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Cross-Domain Conditional Generative Adversarial Networks for Stereoscopic Hyperrealism in Surgical Training
A cross-domain conditional GAN generates stereo-consistent hyperrealistic endoscopic images from phantoms, showing better depth perception and realism than baseline image-to-image methods in evaluations by 6 raters.