Projects:WaveletShrinkage - Revision history

Ygao at 01:00, 16 November 2013

2013-11-16T01:00:31Z

Ygao at 16:13, 12 January 2012

2012-01-12T16:13:32Z

Melonakos: /* Publications */

2010-05-11T19:48:31Z

Publications

Melonakos at 17:39, 25 August 2009

2009-08-25T17:39:40Z

Melonakos at 17:50, 17 July 2009

2009-07-17T17:50:04Z

Melonakos at 19:21, 11 July 2009

2009-07-11T19:21:11Z

Melonakos at 18:13, 16 June 2008

2008-06-16T18:13:31Z

Melonakos at 18:12, 16 June 2008

2008-06-16T18:12:04Z

Xavier: /* Description */

2008-04-28T21:41:25Z

Description

Xavier: /* Description */

2008-04-28T21:36:14Z

Description

← Older revision		Revision as of 01:00, 16 November 2013
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−	Back to [[NA-MIC_Internal_Collaborations:StructuralImageAnalysis\|NA-MIC Collaborations]], [[Algorithm:BU\|~~Boston~~ University Algorithms]]	+	Back to [[NA-MIC_Internal_Collaborations:StructuralImageAnalysis\|NA-MIC Collaborations]], [[Algorithm:Stony Brook\|Stony Brook University Algorithms]]
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← Older revision		Revision as of 16:13, 12 January 2012
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−	Back to [[NA-MIC_Internal_Collaborations:StructuralImageAnalysis\|NA-MIC Collaborations]], [[Algorithm:~~GATech~~\|~~Georgia Tech~~ Algorithms]]	+	Back to [[NA-MIC_Internal_Collaborations:StructuralImageAnalysis\|NA-MIC Collaborations]], [[Algorithm:BU\|Boston University Algorithms]]
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 ''In print''
-[http://www.na-mic.org/publications/pages/display?search=WaveletShrinkage&submit=Search&words=all&title=checked&keywords=checked&authors=checked&abstract=checked&searchbytag=checked&sponsors=checked| NA-MIC Publications Database]
+[http://www.na-mic.org/publications/pages/display?search=WaveletShrinkage&submit=Search&words=all&title=checked&keywords=checked&authors=checked&abstract=checked&searchbytag=checked&sponsors=checked| NA-MIC Publications Database on Wavelet Shrinkage for Shape Analysis]
 [[Category:Shape Analysis]]

← Older revision		Revision as of 17:39, 25 August 2009
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−	Back to [[NA-MIC_Internal_Collaborations:StructuralImageAnalysis\|NA-MIC Collaborations]], [[Algorithm:GATech\|Georgia Tech Algorithms]]	+	Back to [[NA-MIC_Internal_Collaborations:StructuralImageAnalysis\|NA-MIC Collaborations]], [[Algorithm:GATech\|Georgia Tech Algorithms]]
	__NOTOC__		__NOTOC__

← Older revision		Revision as of 17:50, 17 July 2009
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	= Wavelet Shrinkage for Shape Analysis =		= Wavelet Shrinkage for Shape Analysis =
−

	= Description =		= Description =

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 ''In print''
-[http://www.na-mic.org/pages/Special:Publications?text=Projects%3AWaveletShrinkage&submit=Search&words=all&title=checked&keywords=checked&authors=checked&abstract=checked&sponsors=checked&searchbytag=checked|NA-MIC Publications Database]
+[http://www.na-mic.org/pages/Special:Publications?text=Projects%3AWaveletShrinkage&submit=Search&words=all&title=checked&keywords=checked&authors=checked&abstract=checked&sponsors=checked&searchbytag=checked| NA-MIC Publications Database]
 [[Category:Shape Analysis]]

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 = Publications =
-''In press''
+''In print''
-* Bayesian Spherical Wavelet Shrinkage:Applications to shape analysis, X. Le Faucheur, B. Vidakovic, A. Tannenbaum, Proc. of SPIE Optics East, 2007.
 [[Category:Shape Analysis]]

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 Shapes are encoded using spherical wavelets that allow for a multiscale shape representation by decomposing the data both in scale and space using a multiresolution mesh (See Nain ''et al.'' MICCAI 2005). This representation also allows for efficient compression by discarding wavelet coefficients with low values that correspond to irrelevant shape information and high frequency coefficients that represent noisy artifacts. This process is called hard wavelet shrinkage and has been widely researched for traditional types of wavelets, but not much explored for second generation wavelets.
-In the wavelet domain, we model shapes as vectors of coefficients, consisting of the sum of signal part coefficients and coefficients considered as noise:
+In the wavelet domain, we model a shape as a vector of coefficients, consisting in the sum of signal part coefficients and coefficients considered as noise:
 [[Image:Equation_Shape_Representation.jpg| Equation| center]]
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 ''Validation''
-Our validation shows how this new wavelet shrinkage framework outperforms classical compression and denoising methods for shape representation. We apply our method to the denoising of the left hippocampus and caudate nucleus from MRI brain data. In the following figures, we compare our denoising results to those obtained with universal thresholding (Donoho, 1995) and to the method that we had previously developed (SPIE Optics East, 2007), which was based on inter and intra scale dependent shrinkage.
+Our validation shows how this new wavelet shrinkage framework outperforms classical compression and denoising methods for shape representation. We apply our method to the denoising of the left hippocampus and caudate nucleus from MRI brain data. In the following figures, we compare our denoising results to those obtained with universal thresholding (Donoho, 1995) and to the method that we previously developed (SPIE Optics East, 2007), which was based on inter- and intra-scale dependent shrinkage.
 [[Image:Left_Hippocampus_Denoising.jpg| Left Hippocampus Denoising| center]]