RDDM introduces a residual drifting field with attractive and repulsive forces to achieve one-step supervised denoising of low-dose CT, reporting superior PSNR, SSIM, FID of 5.87, and 15 ms inference time.
Competitive performance of a modularized deep neural network compared to commercial algorithms for low-dose ct image reconstruction,
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RDDM: A Residual-Driven Drifting Model for High-Fidelity Low-Dose CT Denoising
RDDM introduces a residual drifting field with attractive and repulsive forces to achieve one-step supervised denoising of low-dose CT, reporting superior PSNR, SSIM, FID of 5.87, and 15 ms inference time.