Research map / Image generation / Image restoration
An Artificial Agent for Robust Image Registration
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use the learned agent instead of human manual registration | 3-D rigid image registration · Spine E1 | success rate (TRE≤10 mm): 70% -> 92% | Helped |
| Use the learned agent instead of human manual registration | 3-D rigid image registration · Heart E2 | success rate (MME≤20 mm): 96% -> 100% | Helped |
| Use the learned agent instead of semantic registration | 3-D rigid image registration · Spine E1 | success rate (TRE≤10 mm): 24% -> 92% | Helped |
| Use the learned agent instead of semantic registration | 3-D rigid image registration · Heart E2 | success rate (MME≤20 mm): 72% -> 100% | Helped |
| Add the refinement CNN after coarse alignment (ablation) | Proposed method · Spine E1 | median TRE (mm): 3.4mm -> 2.5mm | Helped |
| Use DSL rather than DRL for policy training | Registration agent · Modified 2-D spine registration | registration performance | Helped |
Closest papers by meaning
- Deep Learning in Medical Image Registration: Magic or Mirage? (NeurIPS 2024 · similarity 0.87)
- A Plug-and-Play Image Registration Network (ICLR 2024 · similarity 0.87)
- CARL: A Framework for Equivariant Image Registration (CVPR 2025 · similarity 0.85)
- Uncertainty Estimation for Pretrained Medical Image Registration Models via Transformation Equivariance (NeurIPS 2026 · similarity 0.84)
- Intraoperative 2D/3D Image Registration via Differentiable X-ray Rendering (CVPR 2024 · similarity 0.84)
- SACB-Net: Spatial-awareness Convolutions for Medical Image Registration (CVPR 2025 · similarity 0.84)
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