Development and validation of an algorithm for registration of serial 3D MR breast data sets

We report on the development of an algorithm to improve the registration of serial 3D MR breast images using combined global translation and rotation with locally varying parameters as geometric transformations. Several phantom and volunteer data sets were acquired and registered using mutual information as a similarity measure of the matching process. After applying a global translation by using a rigid matcher, optimum horizontal and vertical rotation angles were determined. In case of the phantom measurements, angle optimization was performed for each slice of the 3D data set of the phantom, which was deliberately shifted and rotated around different axes. In case of registration of volunteer data, optimum rotation parameters were calculated for pre-selected equidistant slices of the data set to speed up the calculation time. For slices located between and outside these support slices, the rotation angles were calculated by linear interpolation and extrapolation of the slope of the regression determined by the optimized angles of the support slices. The algorithm improves the registration of serial 3D MR data sets and represents a compromise between a rigid and an elastic 3D matching procedure.