A non-rigid registration method for cerebral DSA images based on forward and inverse stretching – avoiding bilinear interpolation

Abstract

In order to reduce the motion artifact caused by the patient in cerebral DSA images, a non-rigid registration method based on stretching transformation is presented in this paper. Unlike other traditional methods, it does not need bilinear interpolation which is rather time-consuming and even produce 'originally non-existent gray value'. By this method, the mask image is rasterized to generate appropriate control points. The Energy of Histogram of Differences criterion is adopted as similarity measurement, and the Powell algorithm is utilized for acceleration. A forward stretching transformation is used to complete motion estimation and an inverse stretching transformation to generate target image by pixel mapping strategy. This method is effective to maintain the topological relationships of the gray value before and after the image deformation. The mask image remains clear and accurate contours, and the quality of the subtraction image after the registration is favorable. This method can provide support for clinical treatment and diagnosis of cerebral disease.