A deformable image registration algorithm using NURBS

Non-rigid image registration is an interesting and challenging research work in medical image processing, computer vision and remote sensing fields. In order to increase the registration accuracy, this paper designs a composite registration algorithm of a rigid transform and free form deformation. Because NURBS (Non-uniform Rational B Spline) with a non-uniform grid has a higher registration precision and a higher registration speed in comparison with B spline, this paper presents a free form deformation algorithm based on NURBS. On the basis of common similarity metric algorithms, this paper proposes a new MI (mutual information) arithmetic based on the matched region contour. We use snake model to extract the matched region contour in the contour-based MI algorithm. This algorithm combines gray level information of pixels with anatomical information. In consideration of the translation-invariant and rotation-invariant characters of steerable pyramid, we use steerable pyramid to decompose image in multi-scale geometric analysis. In our experiment we give the multi-scale rigid translation results and the experimental results of the NURBS based FFD method quantitatively. The results show that this algorithm improves highly the registration precision.