Marching cubes: A high resolution 3D surface construction algorithm
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
Computer simulation using particles
Computer simulation using particles
SIAM Journal on Scientific and Statistical Computing
Iterative point matching for registration of free-form curves and surfaces
International Journal of Computer Vision
Computational anatomy: an emerging discipline
Quarterly of Applied Mathematics - Special issue on current and future challenges in the applications of mathematics
Group Actions, Homeomorphisms, and Matching: A General Framework
International Journal of Computer Vision - Special issue on statistical and computational theories of vision: Part II
Geodesic Interpolating Splines
EMMCVPR '01 Proceedings of the Third International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition
Computing Large Deformation Metric Mappings via Geodesic Flows of Diffeomorphisms
International Journal of Computer Vision
GPU acceleration of cutoff pair potentials for molecular modeling applications
Proceedings of the 5th conference on Computing frontiers
Large Deformation Diffeomorphic Metric Curve Mapping
International Journal of Computer Vision
Revisiting Histograms and Isosurface Statistics
IEEE Transactions on Visualization and Computer Graphics
Sparse Approximation of Currents for Statistics on Curves and Surfaces
MICCAI '08 Proceedings of the 11th International Conference on Medical Image Computing and Computer-Assisted Intervention, Part II
3D finite difference computation on GPUs using CUDA
Proceedings of 2nd Workshop on General Purpose Processing on Graphics Processing Units
Particle Based Shape Regression of Open Surfaces with Applications to Developmental Neuroimaging
MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part II
Longitudinal cortical registration for developing neonates
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention
Revisiting sorting for GPGPU stream architectures
Proceedings of the 19th international conference on Parallel architectures and compilation techniques
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
A work-efficient GPU algorithm for level set segmentation
Proceedings of the Conference on High Performance Graphics
Unbiased atlas formation via large deformations metric mapping
MICCAI'05 Proceedings of the 8th international conference on Medical image computing and computer-assisted intervention - Volume Part II
IPMI'05 Proceedings of the 19th international conference on Information Processing in Medical Imaging
Deformable templates using large deformation kinematics
IEEE Transactions on Image Processing
Landmark matching via large deformation diffeomorphisms
IEEE Transactions on Image Processing
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Deformable image registration in the presence of considerable contrast differences and large size and shape changes presents significant research challenges. First, it requires a robust registration framework that does not depend on intensity measurements and can handle large nonlinear shape variations. Second, it involves the expensive computation of nonlinear deformations with high degrees of freedom. Often it takes a significant amount of computation time and thus becomes infeasible for practical purposes. In this paper, we present a solution based on two key ideas: a new registration method that generates a mapping between anatomies represented as a multicompartment model of class posterior images and geometries and an implementation of the algorithm using particle mesh approximation on Graphical Processing Units (GPUs) to fulfill the computational requirements. We show results on the registrations of neonatal to 2-year old infant MRIs. Quantitative validation demonstrates that our proposed method generates registrations that better maintain the consistency of anatomical structures over time and provides transformations that better preserve structures undergoing large deformations than transformations obtained by standard intensity-only registration. We also achieve the speedup of three orders of magnitudes compared to a CPU reference implementation, making it possible to use the technique in time-critical applications.