Point-based medical image matching: An automatic algorithm for point extraction

In this paper we address the problem of computing the point correspondences in a reference and subsequent image undergoing an orthogonal, affine, projective, or curved transformation with the aim to register the images. A whole image content based automatic algorithm for extracting point pairs from 2D monomodal medical images is presented. The selection of the most distinctive points from the reference image and the search for their pairs in the subsequent image have two things in common. First, the local operator by which the distinctive points are defined mimics the template matching used to find the point pairs. Second, the same similarity measure is used for both tasks. The results showed that the proposed automatic algorithm for point extraction is accurate and robust. Besides the efficient error handling, the algorithm has the capability to weight each pair according to the distinctiveness of the control point in the reference image, the similarity of the regions which surround the paired points, and the geometric consistency of the registered paired points.