IEEE Transactions on Pattern Analysis and Machine Intelligence
Image selective smoothing and edge detection by nonlinear diffusion
SIAM Journal on Numerical Analysis
A Method for Registration of 3-D Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
The 3L Algorithm for Fitting Implicit Polynomial Curves and Surfaces to Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast Simultaneous Alignment of Multiple Range Images Using Index Images
3DIM '05 Proceedings of the Fifth International Conference on 3-D Digital Imaging and Modeling
Fitting Globally Stabilized Algebraic Surfaces to Range Data
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Shape Registration in Implicit Spaces Using Information Theory and Free Form Deformations
IEEE Transactions on Pattern Analysis and Machine Intelligence
A review of recent range image registration methods with accuracy evaluation
Image and Vision Computing
An Adaptive and Stable Method for Fitting Implicit Polynomial Curves and Surfaces
IEEE Transactions on Pattern Analysis and Machine Intelligence
Adaptively determining degrees of implicit polynomial curves and surfaces
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part II
Automatic registration and fusion of ultrasound with CT for radiotherapy
MICCAI'05 Proceedings of the 8th international conference on Medical image computing and computer-assisted intervention - Volume Part II
IEEE Transactions on Information Technology in Biomedicine
Improving the stability of algebraic curves for applications
IEEE Transactions on Image Processing
Correspondence free registration through a point-to-model distance minimization
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
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A fast registration making use of implicit polynomial (IP) models is helpful for the real-time pose estimation from single clinical free-hand Ultrasound (US) image, because it is superior in the areas such as robustness against image noise, fast registration without enquiring correspondences, and fast IP coefficient transformation. However it might lead to the lack of accuracy or failure registration. In this paper, we present a novel registration method based on a coarse-to-fine IP representation. The approach starts from a high-speed and reliable registration with a coarse (of low degree) IP model and stops when the desired accuracy is achieved by a fine (of high degree) IP model. Over the previous IP-to-point based methods our contributions are: (i) keeping the efficiency without requiring pair-wised correspondences, (ii) enhancing the robustness, and (iii) improving the accuracy. The experimental result demonstrates the good performance of our registration method and its capabilities of overcoming the limitations of unconstrained freehand ultrasound data, resulting in fast, robust and accurate registration.