ArticleSIAM journal on scientific computing : a publication of the Society for Industrial and Applied Mathematics2017
A SEMI-LAGRANGIAN TWO-LEVEL PRECONDITIONED NEWTON-KRYLOV SOLVER FOR CONSTRAINED DIFFEOMORPHIC IMAGE REGISTRATION.
Article in SIAM journal on scientific computing : a publication of the Society for Industrial and Applied Mathematics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Adaptive Riemannian optimization for multi-scale diffeomorphic matching.Nature communications · 2026Article
- CLAIRE-Parallelized Diffeomorphic Image Registration for Large-Scale Biomedical Imaging Applications.Journal of imaging · 2022Article
- Fast GPU 3D diffeomorphic image registration.Journal of parallel and distributed computing · 2021Article
- CLAIRE: Constrained Large Deformation Diffeomorphic Image Registration on Parallel Computing Architectures.Journal of open source software · 2021Article
- Multi-Node Multi-GPU Diffeomorphic Image Registration for Large-Scale Imaging Problems.International Conference for High Performance Computing, Networking, Storage and Analysis : [proceedings]. SC (Conference : Supercomputing) · 2020Article
- A DOMAIN DECOMPOSITION PRECONDITIONING FOR AN INVERSE VOLUME SCATTERING PROBLEM.Inverse problems · 2020Article
- IMAGE-DRIVEN BIOPHYSICAL TUMOR GROWTH MODEL CALIBRATION.SIAM journal on scientific computing : a publication of the Society for Industrial and Applied Mathematics · 2020Article
- Coupling brain-tumor biophysical models and diffeomorphic image registration.Computer methods in applied mechanics and engineering · 2019Article
- CLAIRE: A DISTRIBUTED-MEMORY SOLVER FOR CONSTRAINED LARGE DEFORMATION DIFFEOMORPHIC IMAGE REGISTRATION.SIAM journal on scientific computing : a publication of the Society for Industrial and Applied Mathematics · 2019Article
- A LAGRANGIAN GAUSS-NEWTON-KRYLOV SOLVER FOR MASS- AND INTENSITY-PRESERVING DIFFEOMORPHIC IMAGE REGISTRATION.SIAM journal on scientific computing : a publication of the Society for Industrial and Applied Mathematics · 2017Article
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2 authors.
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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
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