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|a (NLM)16948324
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|a DE-627
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|e rakwb
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|a eng
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|a Oh, Seungseok
|e verfasserin
|4 aut
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|a Multigrid tomographic inversion with variable resolution data and image spaces
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|c 2006
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|a Text
|b txt
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|a ohne Hilfsmittel zu benutzen
|b n
|2 rdamedia
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|a Band
|b nc
|2 rdacarrier
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|a Date Completed 26.09.2006
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|a Date Revised 26.10.2019
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|a published: Print
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|a Citation Status MEDLINE
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|a A multigrid inversion approach that uses variable resolutions of both the data space and the image space is proposed. Since the computational complexity of inverse problems typically increases with a larger number of unknown image pixels and a larger number of measurements, the proposed algorithm further reduces the computation relative to conventional multigrid approaches, which change only the image space resolution at coarse scales. The advantage is particularly important for data-rich applications, where data resolutions may differ for different scales. Applications of the approach to Bayesian reconstruction algorithms in transmission and emission tomography with a generalized Gaussian Markov random field image prior are presented, both with a Poisson noise model and with a quadratic data term. Simulation results indicate that the proposed multigrid approach results in significant improvement in convergence speed compared to the fixed-grid iterative coordinate descent method and a multigrid method with fixed-data resolution
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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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|a Bouman, Charles A
|e verfasserin
|4 aut
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|a Webb, Kevin J
|e verfasserin
|4 aut
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|i Enthalten in
|t IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
|d 1997
|g 15(2006), 9 vom: 12. Sept., Seite 2805-19
|w (DE-627)NLM09821456X
|x 1057-7149
|7 nnns
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|g volume:15
|g year:2006
|g number:9
|g day:12
|g month:09
|g pages:2805-19
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