A PYRAMID APPROACH TO SUBPIXEL REGISTRATION BASED ON INTENSITY

We present an automatic subpixel registration algorithm that minimizes the mean square intensity difference between a reference and a test d ata set, which can be either images (two-dimensional) or volumes (thre e-dimensional), It uses an explicit spline representation of the image s in conjunction with spline processing, and is based on a coarse-to-f ine iterative strategy (pyramid approach). The minimization is perform ed according to a new variation (ML) of the Marquardt-Levenberg algor ithm for nonlinear least-square optimization, The geometric deformatio n model is a global three-dimensional (3-D) affine transformation that can be optionally restricted to rigid-body motion (rotation and trans lation), combined with isometric scaling, It also includes an optional adjustment of image contrast differences, We obtain excellent results for the registration of intramodality positron emission tomography (P ET) and functional magnetic resonance imaging (fMRI) data, We conclude that the multiresolution refinement strategy is more robust than a co mparable single-stage method, being less likely to be trapped into a f alse local optimum, In addition, our improved version of the Marquardt -Levenberg algorithm is faster.