Space-variant Gabor decomposition for filtering 3D medical images.

Darian Onchis, Codruta Istin, Pedro Real
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Abstract

This is an experimental paper in which we introduce the possibility to analyze and to synthesize 3D medical images by using multi-variate 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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用于过滤三维医学图像的空间变型Gabor分解。
这是一篇实验论文,我们介绍了利用高斯窗的多变量Gabor帧来分析和合成三维医学图像的可能性。我们的目的是在空频域中应用一种类似空间变滤波器的操作来校正由不同类型的采集错误损坏的医学图像。为了更好地填充空频平面,Gabor帧是在不可分格上采样的高斯窗构造的。给出了一种具有不可分格的三维gabor框架的可实现解,并对模拟数据进行了数值测试。
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Computer Analysis of Images and Patterns: 19th International Conference, CAIP 2021, Virtual Event, September 28–30, 2021, Proceedings, Part I Computer Analysis of Images and Patterns: 19th International Conference, CAIP 2021, Virtual Event, September 28–30, 2021, Proceedings, Part II Computer Analysis of Images and Patterns: CAIP 2019 International Workshops, ViMaBi and DL-UAV, Salerno, Italy, September 6, 2019, Proceedings Computer Analysis of Images and Patterns: 18th International Conference, CAIP 2019, Salerno, Italy, September 3–5, 2019, Proceedings, Part I Computer Analysis of Images and Patterns: 18th International Conference, CAIP 2019, Salerno, Italy, September 3–5, 2019, Proceedings, Part II
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