Block Matching: Description

MedINRIA provides a rigid and affine registration tool between scalar images.

In order to improve the robustness of rigid registration algorithms in various medical imaging problems, we propose in a general framework built on block matching strategies. This framework combines two stages in a multi-scale hierarchy. The first stage consists in finding for each block (or subregion) of the first image, the most similar subregion in the other image, using a similarity criterion which depends on the nature of the images. The second stage consists in finding the global rigid transformation which best explains most of these local correspondances. This is done with a robust procedure which allows up to 50% of false matches. We show that this approach, besides its simplicity, provides a robust and efficient way to rigidly register images in various situations. This includes for instance the alignment of 2D histological sections for the 3D reconstructions of trimmed organs and tissues, the automatic computation of the mid-sagittal plane in multimodal 3D images of the brain, and the multimodal registration of 3D CT and MR images of the brain. A quantitative evaluation of the results is provided for this last example, as well as a comparison with the classical approaches involving the minimization of a global measure of similarity based on Mutual Information or the Correlation Ratio. This shows a significant improvement of the robustness, for a comparable final accuracy. Although slightly more expensive in terms of computational requirements, the proposed approach can easily be implemented on a parallel architecture, which opens potentialities for real time applications using a large number of processors.

References

  1. Heike Hufnagel, Xavier Pennec, Grégoire Malandain, Hans Handels, and Nicholas Ayache. Non-Linear 2D and 3D Registration Using Block-Matching and B-Splines. In Bildverarbeitung fuer die Medizin 2005, Informatik aktuell, Heidelberg, Germany, pages 325-329, March 2005. Deutsches Krebsforschungszentrum, Springer. [bibtex-entry]


  2. S. Ourselin, A. Roche, S. Prima, and N. Ayache. Block Matching: A General Framework to Improve Robustness of Rigid Registration of Medical Images. In A.M. DiGioia and S. Delp, editors, Third International Conference on Medical Robotics, Imaging And Computer Assisted Surgery (MICCAI 2000), volume 1935 of Lectures Notes in Computer Science, Pittsburgh, Penn, USA, pages 557-566, octobre 11-14 2000. Springer. Keyword(s): registration, matching, histology, MRI. [bibtex-entry]


  3. Heike Hufnagel. Non-linear 2D and 3D Registration Using Block-Matching and B-Splines. Diplomarbeit, University of Luebeck, Lübeck, Germany, 2004. [bibtex-entry]


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