Abstract
This is an experimental paper in which we introduce the possibility to analyze and to synthesize 3D medical images by using multivariate Gabor frames with Gaussian windows. Our purpose is to apply a space-variant filter-like operation in the space-frequency domain to correct medical images corrupted by different types of acquisitions errors. The Gabor frames are constructed with Gaussian windows sampled on non-separable lattices for a better packing of the space-frequency plane. An implementable solution for 3D-Gabor frames with non-separable lattice is given and numerical tests on simulated data are presented.
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Acknowledgments
The first author gratefully acknowledge the support of the Austrian Science Fund (FWF): project number P27516.
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Onchis, D., Istin, C., Real, P. (2017). Space-Variant Gabor Decomposition for Filtering 3D Medical Images. In: Felsberg, M., Heyden, A., Krüger, N. (eds) Computer Analysis of Images and Patterns. CAIP 2017. Lecture Notes in Computer Science(), vol 10425. Springer, Cham. https://doi.org/10.1007/978-3-319-64698-5_38
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DOI: https://doi.org/10.1007/978-3-319-64698-5_38
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