Low-Dose CT Denoising on LDCT
31.748PSNRRED-CNN
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| RED-CNNLearning Paradigm=Supervised, parameters=1.85M2026.01 | 31.748 | 89.6 | 10.686 | |
| Progressive J-invariant Learning + UnetLearning Paradigm=Self-supervised, parameters=31M2026.01 | 31.51 | 89.2 | 10.993 | |
| Progressive J-invariant Learning + RED-CNNLearning Paradigm=Self-supervised, parameters=1.85M2026.01 | 31.261 | 88.9 | 11.324 | |
| Swin-UnetLearning Paradigm=Supervised, parameters=0.95M2026.01 | 31.06 | 89 | 11.558 | |
| Progressive J-invariant Learning + Swin-UnetLearning Paradigm=Self-supervised, parameters=0.95M2026.01 | 30.57 | 88.1 | 12.134 | |
| Cycle GANLearning Paradigm=Supervised, parameters=114M2026.01 | 30.289 | 87.9 | 12.813 | |
| Neighbor2NeighborLearning Paradigm=Self-supervised, parameters=31M2026.01 | 30.078 | 87.6 | 13.099 | |
| Noise2VoidLearning Paradigm=Self-supervised, parameters=31M2026.01 | 29.489 | 86.4 | 14.014 | |
| BM3DLearning Paradigm=Self-supervised, parameters=-2026.01 | 29.103 | 84.2 | 14.281 | |
| LDCT (Dataset)parameters=-2026.01 | 28.842 | 85.6 | 15.16 | |
| LDCT2025.09 | 28.84 | 86 | 15.16 |