Title | ||
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A quadratic majorize-minimize framework for statistical estimation with noisy rician- and noncentral chi-distributed MR images |
Abstract | ||
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The statistics of noisy MR magnitude and square-root sum-of-squares MR images are well-described by the Rice and noncentral chi distributions, respectively. Statistical estimation involving these distributions is complicated by the facts that they have first- and second-order moments that depend nonlinearly on the noiseless image, and can have nonconvex negative log-likelihoods. This paper proposes a new majorize-minimize framework to ease the computational burden associated with statistical estimation involving these distributions. We derive quadratic tangent majorants for the negative log-likelihoods, which enables statistical cost functions to be optimized using a sequence of much simpler least-squares or regularized least-squares surrogate problems. We demonstrate the use of this framework in the context of regularized MR image denoising, with both simulated and experimental data. |
Year | DOI | Venue |
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2013 | 10.1109/ISBI.2013.6556574 | Biomedical Imaging |
Keywords | Field | DocType |
biomedical MRI,image denoising,image sequences,mean square error methods,medical image processing,minimisation,statistical analysis,MR image denoising,first-order moments,image sequence,noiseless image,noisy Rician MR image,noncentral chi-distributed MR image,nonconvex negative log-likelihoods,optimization,quadratic majorize-minimize framework,second-order moments,square-root sum-of-squares MR image,statistical cost functions,statistical estimation,Magnetic Resonance Imaging,Majorize-Minimize Algorithms,Noncentral Chi Distribution,Rice Distribution,Statistical Estimation | Magnitude (mathematics),Pattern recognition,Experimental data,Computer science,Quadratic equation,Minimisation (psychology),Tangent,Image denoising,Artificial intelligence,Statistical analysis,Rician fading | Conference |
ISSN | ISBN | Citations |
1945-7928 | 978-1-4673-6456-0 | 4 |
PageRank | References | Authors |
0.55 | 5 | 2 |
Name | Order | Citations | PageRank |
---|---|---|---|
Divya Varadarajan | 1 | 4 | 0.55 |
Justin P. Haldar | 2 | 350 | 35.40 |