Influence of the boundary conditions on the result of non-linear image registration

The focus of many non-parametric image registration algorithms lies on the solution of non-linear partial differential equations. We offer a simple solution procedure therefor based on discrete Fourier transform. Boundary conditions can strongly influence the result of the registration. The issue is investigated on the example of non-linear curvature-based registration.

[1]  Steven G. Johnson,et al.  FFTW: an adaptive software architecture for the FFT , 1998, Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181).

[2]  Irene A. Stegun,et al.  Pocketbook of mathematical functions , 1984 .

[3]  Niels Jørgen Christensen,et al.  Volume sculpting using the level-set method , 2002, Proceedings SMI. Shape Modeling International 2002.

[4]  Michael I. Miller,et al.  Individualizing Neuroanatomic Atlases Using a Massively Parallel Computer , 1996, Computer.

[5]  L. Horn,et al.  HOW TO QUANTIFY CERVICAL CARCINOMA INVASION FRONTS IN 3D? , 2004, International Journal of Gynecologic Cancer.

[6]  Michael I. Miller,et al.  Deformable templates using large deformation kinematics , 1996, IEEE Trans. Image Process..

[7]  Brian Cabral,et al.  Imaging vector fields using line integral convolution , 1993, SIGGRAPH.

[8]  Steven G. Johnson,et al.  The Design and Implementation of FFTW3 , 2005, Proceedings of the IEEE.

[9]  Morten Bro-Nielsen,et al.  Fast Fluid Registration of Medical Images , 1996, VBC.

[10]  E. Kim.  Whole‐body positron emission tomography and positron emission tomography/computed tomography in gynecologic oncology , 2004, International journal of gynecological cancer : official journal of the International Gynecological Cancer Society.

[11]  Jan Modersitzki,et al.  Numerical Methods for Image Registration , 2004 .

[12]  Yali Amit,et al.  A Nonlinear Variational Problem for Image Matching , 1994, SIAM J. Sci. Comput..

[13]  Volume Assp,et al.  ACOUSTICS. SPEECH. AND SIGNAL PROCESSING , 1983 .

[14]  Ulf-Dietrich Braumann,et al.  Quantification of Tumour Invasion Fronts Using 3D Reconstructed Histological Serial Section , 2004, Bildverarbeitung für die Medizin.

[15]  BrownLisa Gottesfeld.  A survey of image registration techniques , 1992 .

[16]  Jan Modersitzki,et al.  Curvature Based Image Registration , 2004, Journal of Mathematical Imaging and Vision.

[17]  J. Modersitzki,et al.  A unified approach to fast image registration and a new curvature based registration technique , 2004 .

[18]  Markus Löffler,et al.  Three-dimensional reconstruction and quantification of cervical carcinoma invasion fronts from histological serial sections , 2005, IEEE Transactions on Medical Imaging.

[19]  Jan Modersitzki,et al.  Curvature Based Registration with Applications to MR-Mammography , 2002, International Conference on Computational Science.

[20]  Lisa M. Brown,et al.  A survey of image registration techniques , 1992, CSUR.

[21]  Gary E. Christensen,et al.  Deformable Shape Models for Anatomy , 1994 .