SwinMR and SwinGANMR
SwinGANMR builds upon SwinMR by incorporating generative adversarial network training to improve the deformable image registration approach, making them complementary tools where SwinGANMR represents an enhanced variant rather than a direct alternative.
About SwinMR
ayanglab/SwinMR
This is the official implementation of our proposed SwinMR
This tool helps radiologists and clinicians get high-quality MRI scans much faster. It takes raw, undersampled MRI data and quickly reconstructs clear, detailed images, reducing scan times and patient discomfort. This is for medical professionals who perform or interpret MRI scans and need to improve efficiency without sacrificing image quality.
About SwinGANMR
ayanglab/SwinGANMR
Official implementation of SwinGANMR
This project helps medical imaging specialists and radiologists reconstruct high-quality MRI images much faster. It takes raw, undersampled MRI scan data and outputs clear, diagnostic-quality images. This is designed for professionals in medical diagnostics and research who need efficient and accurate MRI results.
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