Title
A Semi-Lagrangian two-level preconditioned Newton-Krylov solver for constrained diffeomorphic image registration.
Abstract
We propose an efficient numerical algorithm for the solution of diffeomorphic image registration problems. We use a variational formulation constrained by a partial differential equation (PDE), where the constraints are a scalar transport equation. We use a pseudospectral discretization in space and second-order accurate semi-Lagrangian time stepping scheme for the transport equations. We solve for a stationary velocity field using a preconditioned, globalized, matrix-free Newton-Krylov scheme. We propose and test a two-level Hessian preconditioner. We consider two strategies for inverting the preconditioner on the coarse grid: A nested preconditioned conjugate gradient method (exact solve) and a nested Chebyshev iterative method (inexact solve) with a fixed number of iterations. We test the performance of our solver in different synthetic and real-world two-dimensional application scenarios. We study grid convergence and computational efficiency of our new scheme. 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. Our improved scheme delivers significant speedups over our original implementation. As a highlight, we observe a 20 x speedup for a two-dimensional, real world multisubject medical image registration problem.
Year
DOI
Venue
2017
10.1137/16M1070475
SIAM JOURNAL ON SCIENTIFIC COMPUTING
Keywords
DocType
Volume
Newton-Krylov method,semi-Lagrangian formulation,KKT preconditioners,constrained diffeomorphic image registration,stationary velocity field registration,optimal control,PDE constrained optimization
Journal
39
Issue
ISSN
Citations 
6
1064-8275
1
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
Andreas Mang13510.57
George Biros293877.86