Two-Parameter Flow Map Learning for Continuous-Time Diffeomorphic Image Registration
Diffeomorphic image registration is central to medical image analysis, enabling anatomically consistent alignment across subjects. Most learning-based diffeomorphic methods model autonomous ODEs(ordinary differential equations) by parameterizing a stationary velocity field and recovering deformations via scaling-and-squaring. While non-autonomous ODEs with time-dependent velocities increase expressiveness, existing approaches rely on numerical integration to implicitly enforce flow structure that entangles model expressiveness with discretization accuracy. We propose a framework to directly learn the continuous-time solution of a non-autonomous ODE formulated as a two-parameterflow map. B...
| Authors | Mohammadjavad Matinkia, Nilanjan Ray |
|---|---|
| Primary category | cs.CV |
| Published | 9 September 2026 |
| Last updated at source | 9 September 2026 |
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