ArticleSIAM journal on scientific computing : a publication of the Society for Industrial and Applied Mathematics2019
CLAIRE: A DISTRIBUTED-MEMORY SOLVER FOR CONSTRAINED LARGE DEFORMATION DIFFEOMORPHIC IMAGE REGISTRATION.
Article in SIAM journal on scientific computing : a publication of the Society for Industrial and Applied Mathematics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Aligning personalized biomarker trajectories onto a common time axis: a connectome-based ODE model for Tau-Amyloid beta dynamics.Medical image analysis · 2025Article
- CLAIRE-Parallelized Diffeomorphic Image Registration for Large-Scale Biomedical Imaging Applications.Journal of imaging · 2022Article
- Partial Differential Equation-Constrained Diffeomorphic Registration from Sum of Squared Differences to Normalized Cross-Correlation, Normalized Gradient Fields, and Mutual Information: A Unifying Framework.Sensors (Basel, Switzerland) · 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
- Fully Automatic Calibration of Tumor-Growth Models Using a Single mpMRI Scan.IEEE transactions on medical imaging · 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
- Multiatlas Calibration of Biophysical Brain Tumor Growth Models with Mass Effect.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention · 2020Article
- A Symmetric Prior for the Regularisation of Elastic Deformations: Improved anatomical plausibility in nonlinear image registration.NeuroImage · 2020Article
- Integrated Biophysical Modeling and Image Analysis: Application to Neuro-Oncology.Annual review of biomedical engineering · 2020Review
- 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
- 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
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Authors and funding
4 authors.
Funding
Abstract
With this work we release CLAIRE, a distributed-memory implementation of an effective solver for constrained large deformation diifeomorphic image registration problems in three dimensions. We consider an optimal control formulation. We invert for a stationary velocity field that parameterizes the deformation map. Our solver is based on a globalized, preconditioned, inexact reduced space Gauss‒Newton‒Krylov scheme. We exploit state-of-the-art techniques in scientific computing to develop an eifective solver that scales to thousands of distributed memory nodes on high-end clusters. We present the formulation, discuss algorithmic features, describe the software package, and introduce an improved preconditioner for the reduced space Hessian to speed up the convergence of our solver. We test registration performance on synthetic and real data. We Demonstrate registration accuracy on several neuroimaging datasets. We compare the performance of our scheme against diiferent flavors of the Demons algorithm for diifeomorphic image registration. We study convergence of our preconditioner and our overall algorithm. We report scalability results on state-of-the-art supercomputing platforms. We Demonstrate that we can solve registration problems for clinically relevant data sizes in two to four minutes on a standard compute node with 20 cores, attaining excellent data fidelity. With the present work we achieve a speedup of (on average) 5× with a peak performance of up to 17× compared to our former work.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.