Abstract
This paper is intended to address three of the most common problems arising in the field of non-rigid biomedical image registration. Firstly, a regularization term based on fractional-order derivatives is proposed. It can be seen as a generalization of the bio-inspired diffusion and curvature smoothing terms but, since it incorporates features of both regularizers, with this approach it is possible to obtain better registration results from a variational point of view. Next, a frequency-domain formulation for the image registration problem is presented. It provides efficient and stable implementations for the considered registration techniques. Finally, a two-step method is proposed for obtaining the optimal values of the registration parameters, because in the literature there is no agreement about which are the optimal values for these parameters, leading the authors to arbitrarily fix them. The resulting registration scheme, after the incorporation of these three strategies, is tested on two biomedical imaging scenarios.
This work is partially supported by the Spanish Ministerio de Ciencia y Tecnología, under grant TEC2006-13338/TCM, and by the Consejería de Educación y Cultura de Murcia, under grant 03122/PI/05.
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Larrey-Ruiz, J., Morales-Sánchez, J., Verdú-Monedero, R. (2007). Novel Strategies for the Optimal Registration of Biomedical Images. In: Mira, J., Álvarez, J.R. (eds) Nature Inspired Problem-Solving Methods in Knowledge Engineering. IWINAC 2007. Lecture Notes in Computer Science, vol 4528. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73055-2_15
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DOI: https://doi.org/10.1007/978-3-540-73055-2_15
Publisher Name: Springer, Berlin, Heidelberg
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