Spatial transformation and registration of brain images using elastically deformable models
Computer Vision and Image Understanding
Non-linear Cerebral Registration with Sulcal Constraints
MICCAI '98 Proceedings of the First International Conference on Medical Image Computing and Computer-Assisted Intervention
Fast Musculoskeletal Registration Based on Shape Matching
MICCAI '08 Proceedings of the 11th International Conference on Medical Image Computing and Computer-Assisted Intervention, Part II
A Fast and Log-Euclidean Polyaffine Framework for Locally Linear Registration
Journal of Mathematical Imaging and Vision
A Log-Euclidean Polyaffine Registration for Articulated Structures in Medical Images
MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part I
A Non-rigid Registration Method for Serial microCT Mouse Hindlimb Images
MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part I
Model-based multi-view fusion of cinematic flow and optical imaging
MICCAI'10 Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part II
Automated registration of whole-body follow-up MicroCT data of mice
MICCAI'11 Proceedings of the 14th international conference on Medical image computing and computer-assisted intervention - Volume Part II
Automatic inter-subject registration of whole body images
WBIR'06 Proceedings of the Third international conference on Biomedical Image Registration
A log-euclidean polyaffine framework for locally rigid or affine registration
WBIR'06 Proceedings of the Third international conference on Biomedical Image Registration
Non-rigid image registration using gaussian mixture models
WBIR'12 Proceedings of the 5th international conference on Biomedical Image Registration
Automated skeleton based multi-modal deformable registration of head&neck datasets
MICCAI'12 Proceedings of the 15th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part II
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This paper describes a new piecewise rotational transformation model for capturing the articulation of joints such as the hip and the knee. While a simple piecewise rigid model can be applied, such models suffer from discontinuities at the motion boundary leading to both folding and stretching. Our model avoids both of these problems by constructing a provably continuous transformation along the motion interface. We embed this transformation model within the robust point matching framework and demonstrate its successful application to both synthetic data, and to serial x-ray CT mouse images. In the later case, our model captures the articulation of six joints, namely the left/right hip, the left/right knee and the left/right ankle. In the future such a model could be used to initialize non-rigid registrations of images from different subjects, as well as, be embedded in intensity-based and integrated registration algorithms. It could also be applied to human data in cases where articulated motion is an issue (e.g. image guided prostate radiotherapy, lower extremity CT angiography).