FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2776756710> ?p ?o ?g. }

• W2776756710 endingPage "1010" @default.
• W2776756710 startingPage "1000" @default.
• W2776756710 abstract "This paper reports on the feasibility of using a quasi-Newton optimization algorithm, limited-memory Broyden-Fletcher-Goldfarb-Shanno with boundary constraints (L-BFGS-B), for penalized image reconstruction problems in emission tomography (ET). For further acceleration, an additional preconditioning technique based on a diagonal approximation of the Hessian was introduced. The convergence rate of L-BFGS-B and the proposed preconditioned algorithm (L-BFGS-B-PC) was evaluated with simulated data with various factors, such as the noise level, penalty type, penalty strength and background level. Data of three 18F-FDG patient acquisitions were also reconstructed. Results showed that the proposed L-BFGS-B-PC outperforms L-BFGS-B in convergence rate for all simulated conditions and the patient data. Based on these results, L-BFGS-B-PC shows promise for clinical application." @default.
• W2776756710 created "2018-01-05" @default.
• W2776756710 creator A5000434695 @default.
• W2776756710 creator A5016217712 @default.
• W2776756710 creator A5035709746 @default.
• W2776756710 creator A5059008417 @default.
• W2776756710 creator A5075569536 @default.
• W2776756710 creator A5078070589 @default.
• W2776756710 creator A5082445591 @default.
• W2776756710 creator A5085748247 @default.
• W2776756710 date "2018-04-01" @default.
• W2776756710 modified "2023-10-15" @default.
• W2776756710 title "Fast Quasi-Newton Algorithms for Penalized Reconstruction in Emission Tomography and Further Improvements via Preconditioning" @default.
• W2776756710 cites W1575258345 @default.
• W2776756710 cites W1983281817 @default.
• W2776756710 cites W1992065047 @default.
• W2776756710 cites W2000359198 @default.
• W2776756710 cites W2005126631 @default.
• W2776756710 cites W2032237670 @default.
• W2776756710 cites W2034135634 @default.
• W2776756710 cites W2036232598 @default.
• W2776756710 cites W2037922117 @default.
• W2776756710 cites W2058839679 @default.
• W2776756710 cites W2068100966 @default.
• W2776756710 cites W2075344979 @default.
• W2776756710 cites W2085075503 @default.
• W2776756710 cites W2091917610 @default.
• W2776756710 cites W2113038890 @default.
• W2776756710 cites W2116670064 @default.
• W2776756710 cites W2117893569 @default.
• W2776756710 cites W2128456478 @default.
• W2776756710 cites W2131501521 @default.
• W2776756710 cites W2133442399 @default.
• W2776756710 cites W2135468550 @default.
• W2776756710 cites W2154744699 @default.
• W2776756710 cites W2155104363 @default.
• W2776756710 cites W2156612134 @default.
• W2776756710 cites W2160260190 @default.
• W2776756710 cites W2162615010 @default.
• W2776756710 cites W2336208919 @default.
• W2776756710 cites W2529357880 @default.
• W2776756710 cites W2608505863 @default.
• W2776756710 cites W2765656669 @default.
• W2776756710 cites W4236796448 @default.
• W2776756710 doi "https://doi.org/10.1109/tmi.2017.2786865" @default.
• W2776756710 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/29610077" @default.
• W2776756710 hasPublicationYear "2018" @default.
• W2776756710 type Work @default.
• W2776756710 sameAs 2776756710 @default.
• W2776756710 citedByCount "13" @default.
• W2776756710 countsByYear W27767567102018 @default.
• W2776756710 countsByYear W27767567102019 @default.
• W2776756710 countsByYear W27767567102020 @default.
• W2776756710 countsByYear W27767567102021 @default.
• W2776756710 countsByYear W27767567102022 @default.
• W2776756710 countsByYear W27767567102023 @default.
• W2776756710 crossrefType "journal-article" @default.
• W2776756710 hasAuthorship W2776756710A5000434695 @default.
• W2776756710 hasAuthorship W2776756710A5016217712 @default.
• W2776756710 hasAuthorship W2776756710A5035709746 @default.
• W2776756710 hasAuthorship W2776756710A5059008417 @default.
• W2776756710 hasAuthorship W2776756710A5075569536 @default.
• W2776756710 hasAuthorship W2776756710A5078070589 @default.
• W2776756710 hasAuthorship W2776756710A5082445591 @default.
• W2776756710 hasAuthorship W2776756710A5085748247 @default.
• W2776756710 hasBestOaLocation W27767567102 @default.
• W2776756710 hasConcept C11413529 @default.
• W2776756710 hasConcept C114954040 @default.
• W2776756710 hasConcept C117896860 @default.
• W2776756710 hasConcept C121332964 @default.
• W2776756710 hasConcept C126255220 @default.
• W2776756710 hasConcept C130367717 @default.
• W2776756710 hasConcept C132721684 @default.
• W2776756710 hasConcept C134306372 @default.
• W2776756710 hasConcept C151319957 @default.
• W2776756710 hasConcept C158622935 @default.
• W2776756710 hasConcept C162324750 @default.
• W2776756710 hasConcept C203616005 @default.
• W2776756710 hasConcept C2524010 @default.
• W2776756710 hasConcept C26517878 @default.
• W2776756710 hasConcept C2777303404 @default.
• W2776756710 hasConcept C28826006 @default.
• W2776756710 hasConcept C31258907 @default.
• W2776756710 hasConcept C33923547 @default.
• W2776756710 hasConcept C38652104 @default.
• W2776756710 hasConcept C41008148 @default.
• W2776756710 hasConcept C50522688 @default.
• W2776756710 hasConcept C57869625 @default.
• W2776756710 hasConcept C62354387 @default.
• W2776756710 hasConcept C62520636 @default.
• W2776756710 hasConcept C74650414 @default.
• W2776756710 hasConcept C85189116 @default.
• W2776756710 hasConceptScore W2776756710C11413529 @default.
• W2776756710 hasConceptScore W2776756710C114954040 @default.
• W2776756710 hasConceptScore W2776756710C117896860 @default.
• W2776756710 hasConceptScore W2776756710C121332964 @default.
• W2776756710 hasConceptScore W2776756710C126255220 @default.
• W2776756710 hasConceptScore W2776756710C130367717 @default.

• next