Research map / Probabilistic and scientific modeling / Differential equations and PDEs
NODEO: A Neural Ordinary Differential Equation Based Optimization Framework for Deformable Image Registration
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Set λ1 to 2 instead of 2.5 (ablation) | NODEO · OASIS | Avg. Dice (28): 0.778 ± 0.026 -> 0.779 ± 0.026 | Helped |
| Set λ1 to 2 instead of 2.5 (ablation) | NODEO · CANDI | Avg. Dice (28): 0.801 ± 0.011 -> 0.802 ± 0.011 | Helped |
| Set λ1 to 2 instead of 2.5 (ablation) | NODEO · CANDI | Avg. Dice (32): 0.760 ± 0.011 -> 0.760 ± 0.011 | No clear effect |
| Add Gaussian smoothing and the negative-Jacobian regularizer (ablation) | NODEO · 2D illustrative image registration | folding / diffeomorphism | Helped |
| Add Gaussian smoothing (ablation) | NODEO · 2D illustrative image registration | spatial smoothness | Helped |
| Add the negative-Jacobian regularizer (ablation) | NODEO · 2D illustrative image registration | diffeomorphism | Helped |
| Use a time-varying system with explicit time embedding instead of a time-invariant system (ablation) | NODEO · 2D multiple-image registration | registration quality | Helped |
| Down-sample the image before the network (ablation) | NODEO · Image-pair registration | runtime: 1/3 | Helped |
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