Automatic extraction of corresponding points for the registration of medical images.
In this paper we address the problem of finding corresponding points in a reference and its subsequent image with the aim of registering the images. A whole-image-content-based automatic algorithm for extracting point pairs from 2-D monomodal medical images has been developed. The properties of point distinctiveness, point pair similarity, and point pair consistency have been incorporated into the steps which lead to the automatic extraction and weighting of point pairs. The selection of the most distinctive points of the reference image, and the search for their corresponding points in the subsequent image, have two things in common. First, the local operator by which the distinctive points are selected mimics the template matching used to find the corresponding points. Second, the same similarity measure is used for both tasks. We have applied the algorithm to a variety of computer-generated and real medical images, and have both qualitatively and quantitatively evaluated its performance. The results show that the proposed automatic algorithm for point extraction is accurate and robust and that it may significantly improve on the accuracy, reproducibility, and speed of the manual extraction of corresponding points.
Likar
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University of Ljubljana, Department of Electrical Engineering, Slovenia.
Pernus
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D000465:Algorithms; D055592:Biophysical Phenomena; D001703:Biophysics; D005069:Evaluation Studies as Topic; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods* / Q000706:statistics & numerical data; D008279:Magnetic Resonance Imaging / Q000379:methods / Q000706:statistics & numerical data; D019047:Phantoms, Imaging; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods