2008
DOI: 10.1117/12.785658
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Statistical simulation of deformations using wavelet independent component analysis

Abstract: Statistical models of deformations are becoming crucial tools for a variety of computer vision applications such as regularization and validation of image registration and segmentation algorithms. In this article, we propose a new approach to effectively represent the statistical properties of high dimensional deformations. In particular, we propose techniques that use independent component analysis (ICA) in conjunction with wavelet packet decomposition. Two different architectures for ICA have been investigat… Show more

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Cited by 1 publication
(1 citation statement)
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“…Rose, and Taylor [16], proposed a statistical model for mammographic appearance using steerable decomposition and PCA modeling. In [17], ElSafi et al proposed a method for statistical simulation of deformations using wavelet Independent Component Analysis. In [18], Xue et al presented a method for simulating of deformations of MR brain images for validation of Atlas-based segmentation and registration algorithms.…”
Section: Related Workmentioning
confidence: 99%
“…Rose, and Taylor [16], proposed a statistical model for mammographic appearance using steerable decomposition and PCA modeling. In [17], ElSafi et al proposed a method for statistical simulation of deformations using wavelet Independent Component Analysis. In [18], Xue et al presented a method for simulating of deformations of MR brain images for validation of Atlas-based segmentation and registration algorithms.…”
Section: Related Workmentioning
confidence: 99%