Constrained Diffeomorphic Image Registration
1 papers with code • 0 benchmarks • 0 datasets
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A Semi-Lagrangian two-level preconditioned Newton-Krylov solver for constrained diffeomorphic image registration
We compare the performance of our solver against our initial implementation that uses the same spatial discretization but a standard, explicit, second-order Runge-Kutta scheme for the numerical time integration of the transport equations and a single-level preconditioner.
An inexact Newton-Krylov algorithm for constrained diffeomorphic image registration
We augment this regularization scheme with a constraint on the divergence of the velocity field rendering the deformation incompressible and thus ensuring that the determinant of the deformation gradient is equal to one, up to the numerical error.
