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231223s2005 xx ||||| 00| ||eng c |
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|a pubmed24n0510.xml
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|a (DE-627)NLM15307521X
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|a (NLM)15646877
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|a DE-627
|b ger
|c DE-627
|e rakwb
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|a eng
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| 100 |
1 |
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|a Oh, Seungseok
|e verfasserin
|4 aut
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|a A general framework for nonlinear multigrid inversion
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|c 2005
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| 336 |
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|a Text
|b txt
|2 rdacontent
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|a ohne Hilfsmittel zu benutzen
|b n
|2 rdamedia
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| 338 |
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|a Band
|b nc
|2 rdacarrier
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| 500 |
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|a Date Completed 10.02.2005
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|a Date Revised 10.12.2019
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|a published: Print
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|a Citation Status MEDLINE
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|a A variety of new imaging modalities, such as optical diffusion tomography, require the inversion of a forward problem that is modeled by the solution to a three-dimensional partial differential equation. For these applications, image reconstruction is particularly difficult because the forward problem is both nonlinear and computationally expensive to evaluate. In this paper, we propose a general framework for nonlinear multigrid inversion that is applicable to a wide variety of inverse problems. The multigrid inversion algorithm results from the application of recursive multigrid techniques to the solution of optimization problems arising from inverse problems. The method works by dynamically adjusting the cost functionals at different scales so that they are consistent with, and ultimately reduce, the finest scale cost functional. In this way, the multigrid inversion algorithm efficiently computes the solution to the desired fine-scale inversion problem. Importantly, the new algorithm can greatly reduce computation because both the forward and inverse problems are more coarsely discretized at lower resolutions. An application of our method to Bayesian optical diffusion tomography with a generalized Gaussian Markov random-field image prior model shows the potential for very large computational savings. Numerical data also indicates robust convergence with a range of initialization conditions for this nonconvex optimization problem
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|a Comparative Study
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|a Evaluation Study
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|a Journal Article
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|a Research Support, U.S. Gov't, Non-P.H.S.
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| 650 |
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|a Validation Study
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| 700 |
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|a Milstein, Adam B
|e verfasserin
|4 aut
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| 700 |
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|a Bouman, Charles A
|e verfasserin
|4 aut
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| 700 |
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|a Webb, Kevin J
|e verfasserin
|4 aut
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| 773 |
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|i Enthalten in
|t IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
|d 1992
|g 14(2005), 1 vom: 25. Jan., Seite 125-40
|w (DE-627)NLM09821456X
|x 1941-0042
|7 nnns
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|g volume:14
|g year:2005
|g number:1
|g day:25
|g month:01
|g pages:125-40
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|d 14
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|e 1
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|h 125-40
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