Automatic extraction of control points for digital subtraction angiography image enhancement

In this paper, a new automatic control point selection and matching technique for digital subtraction angiography image enhancement is proposed. The characteristic of this approach is that it uses features that are based on image moments and are invariant to symmetric blur, translation, and rotation to establish correspondences between matched regions from two X-ray images. The automatic extraction of control points is based on an edge detection approach and on local similarity detection by means of template matching according to a combined invariants-based similarity measure. A new strategy was developed in which a 3-D space-time motion detection algorithm was used for selecting movement points (MPs) belonging to moving structures. The proposed technique has been successfully applied to register several clinical data sets including coronary applications. The experimental results demonstrate the efficiency and accuracy of the algorithm which have outperformed manual registration in terms of root mean square error at the MPs. In addition, the results of the proposed registration algorithm, using the combined invariants-based similarity measure are compared to those of the same proposed algorithm but using the energy of the histogram of differences (EHD) measure. These results clearly indicate that the combined invariants-based measure may be better suited for subpixel registration as it produces more accurate results than EHD.