An adaptive irregular grid approach for 3D deformable image registration.

Deformable registration is an important application in medical image analysis and processing. We propose a physics-based parametric approach for deformable image registration, where non-rigid transformations are computed using an irregular grid of control points distributed within the image domain. The image is modelled as a three-dimensional (3D) homogeneous infinite elastic medium. It is assumed that a Gaussian-shaped force is applied at every control point, where the strengths, directions and influence areas of the forces as well as the positions of the control points are considered as free parameters whose optimization leads to maximization of the similarity measure between the images to be registered. For optimization, a computationally efficient Levenberg-Marquardt method is used. The proposed approach has certain advantages over traditional landmark-based methods or the registration methods based on regular grids, for example B-splines, since comparable results can be achieved by using less control points. Experimental results with 3D clinical images demonstrate that our method is capable of successfully coping with complex registration tasks.