Abstract
In this paper, we embed the minimization scheme of an automatic 3D non-rigid registration method in a multi-scale framework. The initial model formulation was expressed as a robust multiresolution and multigrid minimization scheme. At the finest level of the multiresolution pyramid, we introduce a focusing strategy from coarse-to-fine scales which leads to an improvement of the accuracy in the registration process. A focusing strategy has been tested for a linear and a non-linear scale-space. Results on 3D Ultrasound images are discussed.
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L. Alvarez, J. Weickert, and J. Sanchez. A scale-space approach to nonlocal optical flow calculations. In Scale-Space’ 99, pages 235–246, 1999.
M. Black and A. Rangarajan. On the unification of line processes, outlier rejection and robust statistics with applications in early vision. International Journal of Computer Vision, 19(1):57–91, 1996.
F.L. Bookstein. Principal warps: Thin-plate slines and the decomposition of defomations. IEEE Transactions on Pattern Analysis and Machine Intelligence, 11(6):567–585, 1989.
F. Catté, P.L. Lions, J.M. Morel, and T. Coll. Image selective smoothing and edge detection by nonlinear difusion. SIAM Journal on Numerical analysis, 29:182–193, 1992.
P. Hellier, C. Barillot, E. Mémin, and P. Pérez. An energy-based framework for dense 3D registration of volumetric brain images. In IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), volume II, pages 270–275, Hilton Head Island, South Carolina, USA, June 2000.
B. Horn and B. Schunck. Determining optical flow. Artificial Intelligence, 17:185–203, August 1981.
J. Weber and J. Malik. Robust computation of optical flow in a multi-scale differential framework. International Journal of Computer Vision, 14:67–81, 1995.
E. Mémin and P. Pérez. Dense estimation and object-based segmentation of the optical flow with robust techniques. IEEE Transactions on Image Processing, 7(5):703–719, 1998.
A. Morsy and O. VonRamm. 3D ultrasound tissue motion tracking using correlation search. Ultrasonic Imaging, 20:151–159, 1998.
H.H. Nagel and W. Enkelmann. An investigation of smoothness constraints for the estimation of displacement vector fields from image sequences. IEEE Transactions on Pattern Analysis and Machine Intelligence, 8:565–593, 1986.
W.J. Niessen, J.S. Duncan, M. Nielsen, L.M.J. Florack, ter Haar Romeny B.M, and M.A. Viergever. A multiscale approach to image sequence analysis. Computer Vision and Image Understanding, 65(2):259–268, 1997.
X. Pennec, P. Cachier, and N. Ayache. Understanding the “demon’s algorithm”: 3D non-rigid registration by gradient descent. In MICCAI, pages 597–605, September 1999.
P. Perona and J. Malik. Scale-space and edge detection using anisotropic diffusion. IEEE Transactions on Pattern Analysis and Machine Intelligence, 12(7):629–639, 1990.
M. Strintzis and I. Kokkinidis. Maximum likelihood motion estimation in ultrasound image sequences. IEEE Signal Processing Letters, 4(6):156–157, 1997.
A.P. Witkin. Scale-space filtering. In International Joint Conference on Artificial intelligence, pages 1019–1023, Karlsruhe, W. Germany, 1983.
F. Yeung, S. Levinson, D. Fu, and K. Parker. Feature-adaptive motion tracking of ultrasound image sequences using a deformable mesh. IEEE Transactions on Medical Imaging, 17(6):945–956, 1998.
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© 2001 Springer-Verlag Berlin Heidelberg
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Pratikakis, I., Barillot, C., Hellier, P. (2001). Robust Multi-scale Non-rigid Registration of 3D Ultrasound Images. In: Kerckhove, M. (eds) Scale-Space and Morphology in Computer Vision. Scale-Space 2001. Lecture Notes in Computer Science 2106, vol 2106. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-47778-0_37
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DOI: https://doi.org/10.1007/3-540-47778-0_37
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