FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2890847992> ?p ?o ?g. }

• W2890847992 endingPage "261" @default.
• W2890847992 startingPage "252" @default.
• W2890847992 abstract "Abstract Denoising Magnetic Resonance (MR) image is a challenging task. These images usually comprise more features and structural details when compared to other types of images. These structural details in MR images provide additional information to physicians for better diagnoses and hence there is a need to preserve these details. Over the past few years, various MR image denoising techniques have been evolved. Among them, the techniques based on Non-Local Means (NLM) have achieved excellent performance by exploiting similarity and/or sparseness among the patches. The evolution of NLM filter has changed the paradigm of research in the area of MR imaging. Many variants of NLM algorithms have been developed till today which in addition to retaining the edge/structural features, improve the signal to noise ratio and computational efficiency. The aim of this paper is to provide an exhaustive review of the published literature on NLM based MR image denoising techniques. A critical review and discussion on the advantages and limitations of these techniques are provided with quantitative result analysis." @default.
• W2890847992 created "2018-09-27" @default.
• W2890847992 creator A5002134431 @default.
• W2890847992 creator A5034224505 @default.
• W2890847992 date "2019-01-01" @default.
• W2890847992 modified "2023-10-01" @default.
• W2890847992 title "NLM based magnetic resonance image denoising – A review" @default.
• W2890847992 cites W1840899910 @default.
• W2890847992 cites W1899329334 @default.
• W2890847992 cites W1973207880 @default.
• W2890847992 cites W1973244579 @default.
• W2890847992 cites W1975752945 @default.
• W2890847992 cites W1977066703 @default.
• W2890847992 cites W1978284443 @default.
• W2890847992 cites W1983752053 @default.
• W2890847992 cites W1991696126 @default.
• W2890847992 cites W1995050389 @default.
• W2890847992 cites W1995218003 @default.
• W2890847992 cites W2004418649 @default.
• W2890847992 cites W2006202915 @default.
• W2890847992 cites W2012425475 @default.
• W2890847992 cites W2014940628 @default.
• W2890847992 cites W2016545641 @default.
• W2890847992 cites W2023173554 @default.
• W2890847992 cites W2027096641 @default.
• W2890847992 cites W2032871739 @default.
• W2890847992 cites W2059424622 @default.
• W2890847992 cites W2059784307 @default.
• W2890847992 cites W2065330434 @default.
• W2890847992 cites W2070790070 @default.
• W2890847992 cites W2073660032 @default.
• W2890847992 cites W2075200603 @default.
• W2890847992 cites W2077851444 @default.
• W2890847992 cites W2082291250 @default.
• W2890847992 cites W208252763 @default.
• W2890847992 cites W2092824880 @default.
• W2890847992 cites W2099440229 @default.
• W2890847992 cites W2100031985 @default.
• W2890847992 cites W2105672072 @default.
• W2890847992 cites W2109577576 @default.
• W2890847992 cites W2114487863 @default.
• W2890847992 cites W2119848633 @default.
• W2890847992 cites W2123223785 @default.
• W2890847992 cites W2131752914 @default.
• W2890847992 cites W2132140814 @default.
• W2890847992 cites W2133059825 @default.
• W2890847992 cites W2133394145 @default.
• W2890847992 cites W2133665775 @default.
• W2890847992 cites W2137676365 @default.
• W2890847992 cites W2137901785 @default.
• W2890847992 cites W2138018102 @default.
• W2890847992 cites W2142592339 @default.
• W2890847992 cites W2142931759 @default.
• W2890847992 cites W2144783994 @default.
• W2890847992 cites W2146541446 @default.
• W2890847992 cites W2149857113 @default.
• W2890847992 cites W2151952539 @default.
• W2890847992 cites W2155654390 @default.
• W2890847992 cites W2159269332 @default.
• W2890847992 cites W2160637922 @default.
• W2890847992 cites W2162102990 @default.
• W2890847992 cites W2165170333 @default.
• W2890847992 cites W2168015895 @default.
• W2890847992 cites W2196103734 @default.
• W2890847992 cites W2228580919 @default.
• W2890847992 cites W2276813783 @default.
• W2890847992 cites W2339758283 @default.
• W2890847992 cites W2793332263 @default.
• W2890847992 doi "https://doi.org/10.1016/j.bspc.2018.08.031" @default.
• W2890847992 hasPublicationYear "2019" @default.
• W2890847992 type Work @default.
• W2890847992 sameAs 2890847992 @default.
• W2890847992 citedByCount "49" @default.
• W2890847992 countsByYear W28908479922019 @default.
• W2890847992 countsByYear W28908479922020 @default.
• W2890847992 countsByYear W28908479922021 @default.
• W2890847992 countsByYear W28908479922022 @default.
• W2890847992 countsByYear W28908479922023 @default.
• W2890847992 crossrefType "journal-article" @default.
• W2890847992 hasAuthorship W2890847992A5002134431 @default.
• W2890847992 hasAuthorship W2890847992A5034224505 @default.
• W2890847992 hasConcept C115961682 @default.
• W2890847992 hasConcept C126838900 @default.
• W2890847992 hasConcept C143409427 @default.
• W2890847992 hasConcept C153180895 @default.
• W2890847992 hasConcept C154945302 @default.
• W2890847992 hasConcept C163294075 @default.
• W2890847992 hasConcept C2983327147 @default.
• W2890847992 hasConcept C31972630 @default.
• W2890847992 hasConcept C41008148 @default.
• W2890847992 hasConcept C71924100 @default.
• W2890847992 hasConceptScore W2890847992C115961682 @default.
• W2890847992 hasConceptScore W2890847992C126838900 @default.
• W2890847992 hasConceptScore W2890847992C143409427 @default.
• W2890847992 hasConceptScore W2890847992C153180895 @default.
• W2890847992 hasConceptScore W2890847992C154945302 @default.
• W2890847992 hasConceptScore W2890847992C163294075 @default.
• W2890847992 hasConceptScore W2890847992C2983327147 @default.

• next