In this paper, we present a novel methodology for multimodal non-rigid medical image registration. The proposed approach is based on combining an optical flow technique with a pixel intensity transformation by using a local variability measure, such as statistical variance or Shannon entropy. The methodology is basically composed by three steps: first, we approximate the global deformation using a rigid registration based on a global optimization technique, called particle filtering; second, we transform both target and source images into a new intensity space where they can be compared; and third, we obtain the optical flow between them by using the Horn and Shuck algorithm in an iterative scales-space framework. After these steps, the non-rigid registration is made up by adding the resulting vector fields, computed by the rigid registration, and the optical flow. The proposed algorithm was tested using a synthetic intensity mapping and non-rigid deformation of MRI images. Preliminary results show that the methodology seems to be a good alternative for non-rigid multimodal registration, obtaining an average error of less than two pixels in the estimation of the deformation vector field.

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This paper presents a novel non-rigid multimodal registration method that relies on three basic steps: first, an initial approximation of the deformation field is obtained by a parametric registration technique based on particle filtering; second, an intensity mapping based on local variability measures (LVM) is applied over the two images in order to overcome the multimodal restriction between them; and third, an optical flow method is used in an iterative way to find the remaining displacements of the deformation field. Hence the new methodology offers a solution for multimodal NRR by a quadratic optimisation over a convex surface, which allows independent motion of each pixel, in contrast to methods that parameterise the deformation space. To evaluate the proposed method, a set of magnetic resonance/computed tomography clinical studies (pre- and post-radiotherapy treatment) of three patients with cerebral tumour deformations of the brain structures was employed. The resulting registration was evaluated both qualitatively and quantitatively by standard indices of correspondence over anatomical structures of interest in radiotherapy (brain, tumour and cerebral ventricles). These results showed that one of the proposed LVM (entropy) offers a superior performance in estimating the non-rigid deformation field

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