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.
Cite
CITATION STYLE
Onchis, D., Istin, C., & Real, P. (2017). Space-variant gabor decomposition for filtering 3D medical images. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10425 LNCS, pp. 455–461). Springer Verlag. https://doi.org/10.1007/978-3-319-64698-5_38
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