A comparison of four algorithms for estimating 3-D rigid transformations
BMVC '95 Proceedings of the 1995 British conference on Machine vision (Vol. 1)
Creating and Simulating Skeletal Muscle from the Visible Human Data Set
IEEE Transactions on Visualization and Computer Graphics
Meshless deformations based on shape matching
ACM SIGGRAPH 2005 Papers
Generalized Gradients: Priors on Minimization Flows
International Journal of Computer Vision
FastLSM: fast lattice shape matching for robust real-time deformation
ACM SIGGRAPH 2007 papers
On Linear Variational Surface Deformation Methods
IEEE Transactions on Visualization and Computer Graphics
Generalized surface flows for deformable registration and cortical matching
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention - Volume Part I
Articulated rigid registration for serial lower-limb mouse imaging
MICCAI'05 Proceedings of the 8th international conference on Medical image computing and computer-assisted intervention - Volume Part II
Anatomical modelling of the musculoskeletal system from MRI
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
A log-euclidean polyaffine framework for locally rigid or affine registration
WBIR'06 Proceedings of the Third international conference on Biomedical Image Registration
Efficient Image-Based Proximity Queries with Object-Space Precision
Computer Graphics Forum
Prior knowledge, random walks and human skeletal muscle segmentation
MICCAI'12 Proceedings of the 15th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
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This paper presents a new method for computing elastic and plastic deformations in the context of discrete deformable model-based registration. Internal forces are estimated by averaging local transforms between reference and current particle positions. Our technique can accommodate large non-linear deformations, and is unconditionally stable. Moreover, it is simple to implement and versatile. We show how to tune model stiffness and computational cost, which is important for efficient registration, and demonstrate our technique in the complex problem of inter-patient musculoskeletal registration.