Computing Topology Preservation of RBF Transformations for Landmark-Based Image Registration

In image registration, a proper transformation should be topology preserving. Especially for landmark-based image registration, if the displacement of one landmark is larger enough than those of neighbourhood landmarks, topology violation will be occurred. This paper aims to analyse the topology preservation of some Radial Basis Functions (RBFs) which are used to model deformations in image registration. Matern functions are quite common in the statistic literature (see, e.g. [9, 13]). In this paper, we use them to solve the landmark-based image registration problem. We present the topology preservation properties of RBFs in one landmark and four landmarks model respectively. Numerical results of three kinds of Matern transformations are compared with results of Gaussian, Wendland’s, and Wu’s functions.

[1]  Holger Wendland,et al.  Scattered Data Approximation: Conditionally positive definite functions , 2004 .

[2]  Alessandra De Rossi Medical image registration using compactly supported functions , 2013 .

[3]  Xia Liu,et al.  Topology preservation evaluation of compact-support radial basis functions for image registration , 2011, Pattern Recognit. Lett..

[4]  Roberto Cavoretto,et al.  Analysis of Compactly Supported Transformations for Landmark-based Image Registration , 2013 .

[5]  Gregory E. Fasshauer,et al.  Meshfree Approximation Methods with Matlab , 2007, Interdisciplinary Mathematical Sciences.

[6]  Zongmin Wu,et al.  Compactly supported positive definite radial functions , 1995 .

[7]  Jan Modersitzki,et al.  FAIR: Flexible Algorithms for Image Registration , 2009 .

[8]  Roberto Cavoretto,et al.  Landmark-based image registration using Gneiting's compactly supported functions , 2012 .

[9]  Nira Dyn,et al.  Image Warping by Radial Basis Functions: Application to Facial Expressions , 1994, CVGIP Graph. Model. Image Process..

[10]  Karl Rohr,et al.  Radial basis functions with compact support for elastic registration of medical images , 2001, Image Vis. Comput..

[11]  Roger Woodard,et al.  Interpolation of Spatial Data: Some Theory for Kriging , 1999, Technometrics.

[12]  T. Gneiting,et al.  Matérn Cross-Covariance Functions for Multivariate Random Fields , 2010 .

[13]  Michael L. Stein,et al.  Interpolation of spatial data , 1999 .

[14]  Jan Flusser,et al.  Image registration methods: a survey , 2003, Image Vis. Comput..

[15]  Torsten Werner,et al.  Landmark Based Image Analysis Using Geometric And Intensity Models , 2016 .

[16]  Otmar Scherzer,et al.  Mathematical models for registration and applications to medical imaging , 2006 .

[17]  Roberto Cavoretto,et al.  Local interpolation schemes for landmark-based image registration: A comparison , 2014, Math. Comput. Simul..