Application of new totally structured secant method to registration of time series images

Brain functional imaging is an important tool in the study of nerval science, and it is necessary to register time series images. The new totally structured secant method is adopted to optimize the nonlinear least squares registration criteria, which gets a better approximation to the Hessian of the criteria by secant update, while the conventional method - Gauss-Newton algorithm directly gets rid of the second-order information of the Hessian. At the same time, the update matrix is always symmetrical and positive which makes it reversible, so a descent direction can be found in each step. The simulation registration results show that the algorithm can quickly obtain the best registration parameters with high precision.