Image Deformation Using Velocity Fields: An Exact Solution

In image deformation, one of the challenges is to produce a deformation that preserves image topology. Such deformations are called “homeomorphic”. One method of producing homeomorphic deformations is to move the pixels according to a continuous velocity field defined over the image. The pixels flow along solution curves. Finding the pixel trajectories requires solving a system of differential equations (DEs). Until now, the only known way to accomplish this is to solve the system approximately using numerical time-stepping schemes. However, inaccuracies in the numerical solution can still result in non-homeomorphic deformations. This paper introduces a method of solving the system of DEs exactly over a triangular partition of the image. The results show that the exact method produces homeomorphic deformations in scenarios where the numerical methods fail.

[1]  P. Basser,et al.  In vivo fiber tractography using DT‐MRI data , 2000, Magnetic resonance in medicine.

[2]  C. Poupon,et al.  Regularization of Diffusion-Based Direction Maps for the Tracking of Brain White Matter Fascicles , 2000, NeuroImage.

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

[4]  William E. Lorensen,et al.  Decimation of triangle meshes , 1992, SIGGRAPH.

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

[6]  Fred L. Bookstein,et al.  Principal Warps: Thin-Plate Splines and the Decomposition of Deformations , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[7]  J. Douglas Faires,et al.  Numerical Analysis , 1981 .

[8]  Michael I. Miller,et al.  Landmark matching via large deformation diffeomorphisms , 2000, IEEE Trans. Image Process..

[9]  Edward B. Saff,et al.  Fundamentals of Differential Equations , 1989 .

[10]  P. Basser,et al.  A continuous tensor field approximation of discrete DT-MRI data for extracting microstructural and architectural features of tissue. , 2002, Journal of magnetic resonance.

[11]  Alain Trouvé,et al.  Computing Large Deformation Metric Mappings via Geodesic Flows of Diffeomorphisms , 2005, International Journal of Computer Vision.

[12]  Ruzena Bajcsy,et al.  Multiresolution elastic matching , 1989, Comput. Vis. Graph. Image Process..

[13]  Richard L. Burden,et al.  Numerical analysis: 4th ed , 1988 .

[14]  Michael I. Miller,et al.  Volumetric transformation of brain anatomy , 1997, IEEE Transactions on Medical Imaging.

[15]  J. Miller Numerical Analysis , 1966, Nature.