Abstract
In this paper, 3D voxel-similarity-based (VB) registration algorithms that optimize a feature-space clustering measure are proposed to combine the segmentation and registration process. We present a unifying definition and a classification scheme for existing VB matching criteria and propose a new matching criterion: the entropy of the grey-level scatter-plot. This criterion requires no segmentation or feature extraction and no a priori knowledge of photometric model parameters. The effects of practical implementation issues concerning grey-level resampling, scatter-plot binning, parzen-windowing and resampling frequencies are discussed in detail and evaluated using real world data (CT and MRI).
Directors: André Oosterlinck & Albert L. Baert
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Collignon, A., Vandermeulen, D., Suetens, P., Marchal, G. (1995). 3D Multi-Modality Medical Image Registration Using Feature Space Clustering. In: Ayache, N. (eds) Computer Vision, Virtual Reality and Robotics in Medicine. CVRMed 1995. Lecture Notes in Computer Science, vol 905. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-49197-2_22
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DOI: https://doi.org/10.1007/978-3-540-49197-2_22
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