Difference between revisions of "Projects:ShapeAnalysisWithOvercompleteWavelets"

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(New page: Back to NA-MIC_Collaborations, MIT Algorithms We propose a unified framework for computing atlases from manually labeled data sets at various d...)
 
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Back to [[NA-MIC_Collaborations|NA-MIC_Collaborations]], [[Algorithm:MIT|MIT Algorithms]]
 
Back to [[NA-MIC_Collaborations|NA-MIC_Collaborations]], [[Algorithm:MIT|MIT Algorithms]]
  
We propose a unified framework for computing atlases from manually labeled data sets at various degrees of “sharpness” and the joint registration and segmentation of a new brain with these atlases. In non-rigid registration, the tradeoff between warp regularization and image fidelity is typically set empirically. In segmentation, this leads to a probabilistic atlas of arbitrary “sharpness”: weak regularization results in well-aligned training images, producing a “sharp” atlas; strong regularization yields a “blurry” atlas. We study the effects of this tradeoff in the context of cortical surface parcellation, but the framework applies to volume registration as well.  
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In this work, we extend the Euclidean wavelets to the sphere. The resulting over-complete spherical wavelets are invariant to rotation of the parameterization of the original spherical image. We apply the over-complete spherical wavelet to cortical folding development and show significantly consistent results as well as improved sensitivity compared with the previous methods of using bi-orthogonal spherical wavelet. In particular, we were able to detect developmental asymmetry in the left and right hemispheres.
  
 
= Description =
 
= Description =
  
We compare three special cases of our framework, namely:
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Blah
 
 
(1) Progressive registration of a new brain to increasingly “sharp” atlases using increasingly
 
flexible warps, by initializing each registration stage with the optimal warps from
 
a “blurrier” atlas. We call this multiple atlases, multiple warp scales (MAMS).
 
 
 
(2) Progressive registration to a single atlas with increasingly
 
flexible warps. We call this single atlas, multiple warp scales (SAMS).
 
 
 
(3) Registration to a single atlas with fixed constrained warps. We call this single atlas, single warp scale (SASS).
 
 
 
We use dice as the measure of segmentation quality. From the graph below, we note that the optimal parcellation algorithm in all three cases yield a statistically significant improvement over a state-of-the-art benchmark parcellation algorithm [1,2]. The optimal algorithms correspond to a unique balance between atlas “sharpness” and warp regularization.
 
 
 
[[Image:AvgResults.jpg|thumb|center|300px|Plot of Dice as a function of the warp smoothness S. Note that S is on a log scale. <math>\alpha</math> corresponds to the sharpness of the atlas used.]]
 
  
 
= Key Investigator =
 
= Key Investigator =
  
MIT: B.T. Thomas Yeo, Mert Sabuncu, Rahul Desikan, Bruce Fischl, Polina Golland
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MIT: Peng Yu, B.T. Thomas Yeo, Ellen Grant, Bruce Fischl, Polina Golland
  
 
= Publication =
 
= Publication =
  
[1] B. Fischl et al. Automatically Parcellating the Human cerebral Cortex. Cerebral
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[1] D. Nain, S. Haker, A. Bobick, and A. Tannenbaum, "Multiscale 3-d
Cortex, 14:11-22, 2004.
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shape representation and segmentation using spherical wavelets," IEEE
 
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Transaction on Medical Imaging, vol. 26, pp. 598-618, 2007.
[2] Desikan et al. An auto. labeling system for subdividing the human cerebral cortex
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[2] B.T.T. Yeo, W. Ou, P. Golland. On the Construction of Invertible Filter Banks on the 2-Sphere. Yeo, Ou and Golland. Accepted to the IEEE Transactions on Image Processing [In Press]
on MRI scans into gyral based regions of interest. NeuroImage, 31:968-980, 2006.
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[3] P. Yu, B.T.T. Yeo, P.E. Grant, B. Fischl, P. Golland. Cortical Folding Development Study based on Over-Complete Spherical Wavelets. In Proceedings of MMBIA: IEEE Computer Society Workshop on Mathematical Methods in Biomedical Image Analysis, 2007.
 
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[4] P. Yu, P. E. Grant, Y. Qi, X. Han, et al., "Cortical surface shape
[3] B.T.T. Yeo, M.R. Sabuncu, R. Desikan, B. Fischl, P. Golland. Effects of Registration Regularization and Atlas Sharpness on Segmentation Accuracy. In Proceedings of MICCAI: International Conference on Medical Image Computing and Computer Assisted Intervention, 683-691, 2007. '''MICCAI Young Scientist Award.'''
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analysis based on spherical wavelets," IEEE Transaction on Medical
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Imaging, vol. 26, pp. 582-97, 2007.
  
 
[http://www.na-mic.org/Special:Publications?text=Projects%3ARegistrationRegularization&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/Special:Publications?text=Projects%3ARegistrationRegularization&submit=Search&words=all&title=checked&keywords=checked&authors=checked&abstract=checked&sponsors=checked&searchbytag=checked| NA-MIC Publications Database]
  
 
= Links =
 
= Links =

Revision as of 19:51, 9 November 2007

Home < Projects:ShapeAnalysisWithOvercompleteWavelets

Back to NA-MIC_Collaborations, MIT Algorithms

In this work, we extend the Euclidean wavelets to the sphere. The resulting over-complete spherical wavelets are invariant to rotation of the parameterization of the original spherical image. We apply the over-complete spherical wavelet to cortical folding development and show significantly consistent results as well as improved sensitivity compared with the previous methods of using bi-orthogonal spherical wavelet. In particular, we were able to detect developmental asymmetry in the left and right hemispheres.

Description

Blah

Key Investigator

MIT: Peng Yu, B.T. Thomas Yeo, Ellen Grant, Bruce Fischl, Polina Golland

Publication

[1] D. Nain, S. Haker, A. Bobick, and A. Tannenbaum, "Multiscale 3-d shape representation and segmentation using spherical wavelets," IEEE Transaction on Medical Imaging, vol. 26, pp. 598-618, 2007. [2] B.T.T. Yeo, W. Ou, P. Golland. On the Construction of Invertible Filter Banks on the 2-Sphere. Yeo, Ou and Golland. Accepted to the IEEE Transactions on Image Processing [In Press] [3] P. Yu, B.T.T. Yeo, P.E. Grant, B. Fischl, P. Golland. Cortical Folding Development Study based on Over-Complete Spherical Wavelets. In Proceedings of MMBIA: IEEE Computer Society Workshop on Mathematical Methods in Biomedical Image Analysis, 2007. [4] P. Yu, P. E. Grant, Y. Qi, X. Han, et al., "Cortical surface shape analysis based on spherical wavelets," IEEE Transaction on Medical Imaging, vol. 26, pp. 582-97, 2007.

NA-MIC Publications Database

Links