FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2901801560> ?p ?o ?g. }

• W2901801560 endingPage "386" @default.
• W2901801560 startingPage "380" @default.
• W2901801560 abstract "ABSTRACT Introduction : Golden retriever muscular dystrophy (GRMD), an X‐linked recessive disorder, causes similar phenotypic features to Duchenne muscular dystrophy (DMD). There is currently a need for a quantitative and reproducible monitoring of disease progression for GRMD and DMD. Methods : To assess severity in the GRMD, we analyzed texture features extracted from multi‐parametric MRI (T1w, T2w, T1m, T2m, and Dixon images) using 5 feature extraction methods and classified using support vector machines. Results : A single feature from qualitative images can provide 89% maximal accuracy. Furthermore, 2 features from T1w, T2m, or Dixon images provided highest accuracy. When considering a tradeoff between scan‐time and computational complexity, T2m images provided good accuracy at a lower acquisition and processing time and effort. Conclusions : The combination of MRI texture features improved the classification accuracy for assessment of disease progression in GRMD with evaluation of the heterogenous nature of skeletal muscles as reflection of the histopathological changes. Muscle Nerve 59 :380–386, 2019" @default.
• W2901801560 created "2018-11-29" @default.
• W2901801560 creator A5004093378 @default.
• W2901801560 creator A5006980883 @default.
• W2901801560 creator A5024277918 @default.
• W2901801560 creator A5028951034 @default.
• W2901801560 creator A5060212143 @default.
• W2901801560 creator A5064208221 @default.
• W2901801560 creator A5075878616 @default.
• W2901801560 date "2019-01-13" @default.
• W2901801560 modified "2023-10-17" @default.
• W2901801560 title "Texture as an imaging biomarker for disease severity in golden retriever muscular dystrophy" @default.
• W2901801560 cites W1524530894 @default.
• W2901801560 cites W1588504034 @default.
• W2901801560 cites W1922964466 @default.
• W2901801560 cites W1935523855 @default.
• W2901801560 cites W1961133757 @default.
• W2901801560 cites W1961515822 @default.
• W2901801560 cites W1967943762 @default.
• W2901801560 cites W1973408614 @default.
• W2901801560 cites W1975139695 @default.
• W2901801560 cites W1984417910 @default.
• W2901801560 cites W1986814309 @default.
• W2901801560 cites W1995068750 @default.
• W2901801560 cites W1997789665 @default.
• W2901801560 cites W1999317063 @default.
• W2901801560 cites W2001604199 @default.
• W2901801560 cites W2003304826 @default.
• W2901801560 cites W2018722071 @default.
• W2901801560 cites W2019190989 @default.
• W2901801560 cites W2020713997 @default.
• W2901801560 cites W2023698258 @default.
• W2901801560 cites W2026084370 @default.
• W2901801560 cites W2034180487 @default.
• W2901801560 cites W2039051707 @default.
• W2901801560 cites W2042331443 @default.
• W2901801560 cites W2044465660 @default.
• W2901801560 cites W2051152513 @default.
• W2901801560 cites W2054736119 @default.
• W2901801560 cites W2059156500 @default.
• W2901801560 cites W2062442451 @default.
• W2901801560 cites W2073563966 @default.
• W2901801560 cites W2073885735 @default.
• W2901801560 cites W2077301034 @default.
• W2901801560 cites W2085943981 @default.
• W2901801560 cites W2086023949 @default.
• W2901801560 cites W2087739532 @default.
• W2901801560 cites W2093103229 @default.
• W2901801560 cites W2097155618 @default.
• W2901801560 cites W2104095591 @default.
• W2901801560 cites W2108034706 @default.
• W2901801560 cites W2111218581 @default.
• W2901801560 cites W2116484895 @default.
• W2901801560 cites W2117340355 @default.
• W2901801560 cites W2124156889 @default.
• W2901801560 cites W2130884450 @default.
• W2901801560 cites W2133287637 @default.
• W2901801560 cites W2139212933 @default.
• W2901801560 cites W2164104688 @default.
• W2901801560 cites W2171418530 @default.
• W2901801560 cites W2264440929 @default.
• W2901801560 cites W2271760492 @default.
• W2901801560 cites W2277280343 @default.
• W2901801560 cites W2281104138 @default.
• W2901801560 cites W2341335317 @default.
• W2901801560 cites W2424490565 @default.
• W2901801560 cites W2522240791 @default.
• W2901801560 cites W2615551774 @default.
• W2901801560 cites W2724098443 @default.
• W2901801560 cites W2741280726 @default.
• W2901801560 cites W2891258460 @default.
• W2901801560 cites W3022997872 @default.
• W2901801560 cites W4236304200 @default.
• W2901801560 cites W804694437 @default.
• W2901801560 cites W910144762 @default.
• W2901801560 doi "https://doi.org/10.1002/mus.26386" @default.
• W2901801560 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/30461036" @default.
• W2901801560 hasPublicationYear "2019" @default.
• W2901801560 type Work @default.
• W2901801560 sameAs 2901801560 @default.
• W2901801560 citedByCount "7" @default.
• W2901801560 countsByYear W29018015602019 @default.
• W2901801560 countsByYear W29018015602020 @default.
• W2901801560 countsByYear W29018015602021 @default.
• W2901801560 countsByYear W29018015602022 @default.
• W2901801560 crossrefType "journal-article" @default.
• W2901801560 hasAuthorship W2901801560A5004093378 @default.
• W2901801560 hasAuthorship W2901801560A5006980883 @default.
• W2901801560 hasAuthorship W2901801560A5024277918 @default.
• W2901801560 hasAuthorship W2901801560A5028951034 @default.
• W2901801560 hasAuthorship W2901801560A5060212143 @default.
• W2901801560 hasAuthorship W2901801560A5064208221 @default.
• W2901801560 hasAuthorship W2901801560A5075878616 @default.
• W2901801560 hasBestOaLocation W29018015601 @default.
• W2901801560 hasConcept C126322002 @default.
• W2901801560 hasConcept C142724271 @default.
• W2901801560 hasConcept C153180895 @default.
• W2901801560 hasConcept C154945302 @default.

• next