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]]
  
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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 =
  
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We compare three special cases of our framework, namely:
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Blah
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(1) Progressive registration of a new brain to increasingly “sharp” atlases using increasingly
 
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flexible warps, by initializing each registration stage with the optimal warps from
 
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a “blurrier” atlas. We call this multiple atlases, multiple warp scales (MAMS).
 
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(2) Progressive registration to a single atlas with increasingly
 
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flexible warps. We call this single atlas, multiple warp scales (SAMS).
 
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(3) Registration to a single atlas with fixed constrained warps. We call this single atlas, single warp scale (SASS).
 
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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.
 
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[[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 =
  
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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 =
  
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[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
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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.
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[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]
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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
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[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

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