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CT Super-resolution GAN Constrained by the Identical, Residual, and Cycle Learning Ensemble (GAN-CIRCLE)
RPI ID: 2019-005-201 / 2019-005-601Innovation Summary:This invention introduces a deep learning framework called GAN-Circle for super-resolution reconstruction in computed tomography (CT) imaging. The system is based on a generative adversarial network (GAN) architecture constrained by three synergistic learning strategies: identical mapping, residual...
Published: 7/21/2025
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Updated: 7/3/2025
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Inventor(s): Ge Wang, Chenyu You, Wenxiang Cong, Hongming Shan, Guang Li
Keywords(s): High-resolution CT image, Image super resolution, low-resolution CT image
Category(s): Computational Science and Engineering
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