Regularization, Scale-Space, and Edge Detection Filters
Journal of Mathematical Imaging and Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Nonrigid 3-D/2-D Registration of Images Using Statistical Models
MICCAI '99 Proceedings of the Second International Conference on Medical Image Computing and Computer-Assisted Intervention
Automatic Construction of 3D Statistical Deformation Models Using Non-rigid Registration
MICCAI '01 Proceedings of the 4th International Conference on Medical Image Computing and Computer-Assisted Intervention
Active Appearance Models Revisited
International Journal of Computer Vision
Non-parametric diffeomorphic image registration with the demons algorithm
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention
Deformable 2D-3D registration of the pelvis with a limited field of view, using shape statistics
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention
3D reconstruction of both shape and bone mineral density distribution of the femur from DXA images
ISBI'10 Proceedings of the 2010 IEEE international conference on Biomedical imaging: from nano to Macro
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This paper presents a new approach for reconstructing a patient-specific shape model and internal relative intensity distribution of the proximal femur from a limited number (e.g., 2) of calibrated C-arm images or X-ray radiographs. Our approach uses independent shape and appearance models that are learned from a set of training data to encode the a priori information about the proximal femur. An intensity-based non-rigid 2D-3D registration algorithm is then proposed to deformably fit the learned models to the input images. The fitting is conducted iteratively by minimizing the dissimilarity between the input images and the associated digitally reconstructed radiographs of the learned models together with regularization terms encoding the strain energy of the forward deformation and the smoothness of the inverse deformation. Comprehensive experiments conducted on images of cadaveric femurs and on clinical datasets demonstrate the efficacy of the present approach.