Robust medical image elastic registration using global optimisation strategy in frequency domain

Abstract A new global optimisation strategy in frequency domain (GOFD) is presented and applied in medical image elastic registration. The method is consists of a global optimisation phase for rough searching and a local optimisation phase for fine searching. Rough searching is based on the random sampling technique in the frequency domain. According to the sampling theory, when the sampling frequency is higher than twice the maximum frequency of a function, the function can be completely reconstructed from these finite sampling points. The maximum (or minimum) value of the function at these finite sampling points is approximately in the global extreme. To obtain the exact global extreme, fine searching is performed in the small neighbourhood of the point corresponding to the approximate global maximum value. The new method presented can theoretically ensure that the global optimisation solution is found. The experiments show that our new method is more robust and accurate than other elastic registration algorithms.

[1]  Matthias Otte,et al.  Elastic registration of fMRI data using Bezier-spline transformations , 2001, IEEE Transactions on Medical Imaging.

[2]  Michael Brady,et al.  Regularized B-spline deformable registration for respiratory motion correction in PET images , 2008, 2008 IEEE Nuclear Science Symposium Conference Record.

[3]  Paul Suetens,et al.  Comparative evaluation of multiresolution optimization strategies for multimodality image registration by maximization of mutual information , 1999, Medical Image Anal..

[4]  E. Hoffman,et al.  Mass preserving nonrigid registration of CT lung images using cubic B-spline. , 2009, Medical physics.

[5]  Daniel Rueckert,et al.  Nonrigid registration using free-form deformations: application to breast MR images , 1999, IEEE Transactions on Medical Imaging.

[6]  Torsten Rohlfing,et al.  Volume-preserving nonrigid registration of MR breast images using free-form deformation with an incompressibility constraint , 2003, IEEE Transactions on Medical Imaging.

[7]  Jan Kybic,et al.  Bootstrap Resampling for Image Registration Uncertainty Estimation Without Ground Truth , 2010, IEEE Transactions on Image Processing.

[8]  Terry M. Peters,et al.  High-performance medical image registration using new optimization techniques , 2006, IEEE Transactions on Information Technology in Biomedicine.

[9]  Marc L. Kessler,et al.  A Stochastic Approach to Estimate the UncertaintyInvolved in B-Spline Image Registration , 2009, IEEE Transactions on Medical Imaging.

[10]  Patrick Clarysse,et al.  A review of cardiac image registration methods , 2002, IEEE Transactions on Medical Imaging.

[11]  Stephen M. Smith,et al.  A global optimisation method for robust affine registration of brain images , 2001, Medical Image Anal..

[12]  Josien P. W. Pluim,et al.  Evaluation of Optimization Methods for Nonrigid Medical Image Registration Using Mutual Information and B-Splines , 2007, IEEE Transactions on Image Processing.

[13]  Jürgen R. Reichenbach,et al.  Development and validation of an algorithm for registration of serial 3D MR breast data sets , 2007, Magnetic Resonance Materials in Physics, Biology and Medicine.

[14]  M. Narasimha Murty,et al.  A stochastic connectionist approach for global optimization with application to pattern clustering , 2000, IEEE Trans. Syst. Man Cybern. Part B.

[15]  Ponnada A Narayana,et al.  Global optimization of mutual information: application to three-dimensional retrospective registration of magnetic resonance images. , 2002, Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society.

[16]  Polina Golland,et al.  Free-Form B-spline Deformation Model for Groupwise Registration. , 2007, Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention.

[17]  Torsten Rohlfing,et al.  Nonrigid image registration in shared-memory multiprocessor environments with application to brains, breasts, and bees , 2003, IEEE Transactions on Information Technology in Biomedicine.

[18]  Michael Unser,et al.  Fast parametric elastic image registration , 2003, IEEE Trans. Image Process..