Joint low-rank prior and difference of Gaussian filter for magnetic resonance image denoising
Joint low-rank prior and difference of Gaussian filter for magnetic resonance image denoising
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Publisher
Berlin/Heidelberg: Springer Berlin Heidelberg
Journal title
Language
English
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Publisher
Berlin/Heidelberg: Springer Berlin Heidelberg
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Scope and Contents
Contents
The low-rank matrix approximation (LRMA) is an efficient image denoising method to reduce additive Gaussian noise. However, the existing low-rank matrix approximation does not perform well in terms of Rician noise removal for magnetic resonance imaging (MRI). To this end, we propose a novel MR image denoising approach based on the extended differen...
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Full title
Joint low-rank prior and difference of Gaussian filter for magnetic resonance image denoising
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Record Identifier
TN_cdi_proquest_miscellaneous_2489597280
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_miscellaneous_2489597280
Other Identifiers
ISSN
0140-0118
E-ISSN
1741-0444
DOI
10.1007/s11517-020-02312-8
