FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W1999136737> ?p ?o ?g. }

• W1999136737 endingPage "6867" @default.
• W1999136737 startingPage "6849" @default.
• W1999136737 abstract "The purpose of this study was to develop and evaluate the hybrid scatter correction algorithm (HSC) for CT imaging. Therefore, two established ways to perform scatter correction, i.e. physical scatter correction based on Monte Carlo simulations and a convolution-based scatter correction algorithm, were combined in order to perform an object-dependent, fast and accurate scatter correction. Based on a reconstructed CT volume, patient-specific scatter intensity is estimated by a coarse Monte Carlo simulation that uses a reduced amount of simulated photons in order to reduce the simulation time. To further speed up the Monte Carlo scatter estimation, scatter intensities are simulated only for a fraction of all projections. In a second step, the high noise estimate of the scatter intensity is used to calibrate the open parameters in a convolution-based algorithm which is then used to correct measured intensities for scatter. Furthermore, the scatter-corrected intensities are used in order to reconstruct a scatter-corrected CT volume data set. To evaluate the scatter reduction potential of HSC, we conducted simulations in a clinical CT geometry and measurements with a flat detector CT system. In the simulation study, HSC-corrected images were compared to scatter-free reference images. For the measurements, no scatter-free reference image was available. Therefore, we used an image corrected with a low-noise Monte Carlo simulation as a reference. The results show that the HSC can significantly reduce scatter artifacts. Compared to the reference images, the error due to scatter artifacts decreased from 100% for uncorrected images to a value below 20% for HSC-corrected images for both the clinical (simulated data) and the flat detector CT geometry (measurement). Compared to a low-noise Monte Carlo simulation, with the HSC the number of photon histories can be reduced by about a factor of 100 per projection without losing correction accuracy. Furthermore, it was sufficient to calibrate the parameters in the convolution model at an angular increment of about 20°. The reduction of the simulated photon histories together with the reduced amount of simulated Monte Carlo scatter projections decreased the total runtime of the scatter correction by about two orders of magnitude for the cases investigated here when using the HSC instead of a low-noise Monte Carlo simulation for scatter correction." @default.
• W1999136737 created "2016-06-24" @default.
• W1999136737 creator A5019247249 @default.
• W1999136737 creator A5036808009 @default.
• W1999136737 date "2012-10-05" @default.
• W1999136737 modified "2023-10-16" @default.
• W1999136737 title "Hybrid scatter correction for CT imaging" @default.
• W1999136737 cites W1964760340 @default.
• W1999136737 cites W1977836277 @default.
• W1999136737 cites W1979676024 @default.
• W1999136737 cites W1983619527 @default.
• W1999136737 cites W1988908093 @default.
• W1999136737 cites W1992705935 @default.
• W1999136737 cites W2018670706 @default.
• W1999136737 cites W2021157360 @default.
• W1999136737 cites W2025257312 @default.
• W1999136737 cites W2033978387 @default.
• W1999136737 cites W2034707285 @default.
• W1999136737 cites W2036494829 @default.
• W1999136737 cites W2038253228 @default.
• W1999136737 cites W2043193153 @default.
• W1999136737 cites W2044918922 @default.
• W1999136737 cites W2054663128 @default.
• W1999136737 cites W2056637494 @default.
• W1999136737 cites W2065401809 @default.
• W1999136737 cites W2065646652 @default.
• W1999136737 cites W2066270606 @default.
• W1999136737 cites W2073658503 @default.
• W1999136737 cites W2077699569 @default.
• W1999136737 cites W2078977199 @default.
• W1999136737 cites W2079127706 @default.
• W1999136737 cites W2087991208 @default.
• W1999136737 cites W2098494036 @default.
• W1999136737 cites W2128930532 @default.
• W1999136737 cites W2149489589 @default.
• W1999136737 cites W2154129661 @default.
• W1999136737 cites W2156025556 @default.
• W1999136737 doi "https://doi.org/10.1088/0031-9155/57/21/6849" @default.
• W1999136737 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/23038048" @default.
• W1999136737 hasPublicationYear "2012" @default.
• W1999136737 type Work @default.
• W1999136737 sameAs 1999136737 @default.
• W1999136737 citedByCount "44" @default.
• W1999136737 countsByYear W19991367372014 @default.
• W1999136737 countsByYear W19991367372015 @default.
• W1999136737 countsByYear W19991367372016 @default.
• W1999136737 countsByYear W19991367372017 @default.
• W1999136737 countsByYear W19991367372018 @default.
• W1999136737 countsByYear W19991367372019 @default.
• W1999136737 countsByYear W19991367372020 @default.
• W1999136737 countsByYear W19991367372021 @default.
• W1999136737 countsByYear W19991367372022 @default.
• W1999136737 countsByYear W19991367372023 @default.
• W1999136737 crossrefType "journal-article" @default.
• W1999136737 hasAuthorship W1999136737A5019247249 @default.
• W1999136737 hasAuthorship W1999136737A5036808009 @default.
• W1999136737 hasConcept C105795698 @default.
• W1999136737 hasConcept C11413529 @default.
• W1999136737 hasConcept C115961682 @default.
• W1999136737 hasConcept C120665830 @default.
• W1999136737 hasConcept C121332964 @default.
• W1999136737 hasConcept C154945302 @default.
• W1999136737 hasConcept C191486275 @default.
• W1999136737 hasConcept C19499675 @default.
• W1999136737 hasConcept C33923547 @default.
• W1999136737 hasConcept C35777598 @default.
• W1999136737 hasConcept C41008148 @default.
• W1999136737 hasConcept C45347329 @default.
• W1999136737 hasConcept C50644808 @default.
• W1999136737 hasConcept C94915269 @default.
• W1999136737 hasConcept C99498987 @default.
• W1999136737 hasConceptScore W1999136737C105795698 @default.
• W1999136737 hasConceptScore W1999136737C11413529 @default.
• W1999136737 hasConceptScore W1999136737C115961682 @default.
• W1999136737 hasConceptScore W1999136737C120665830 @default.
• W1999136737 hasConceptScore W1999136737C121332964 @default.
• W1999136737 hasConceptScore W1999136737C154945302 @default.
• W1999136737 hasConceptScore W1999136737C191486275 @default.
• W1999136737 hasConceptScore W1999136737C19499675 @default.
• W1999136737 hasConceptScore W1999136737C33923547 @default.
• W1999136737 hasConceptScore W1999136737C35777598 @default.
• W1999136737 hasConceptScore W1999136737C41008148 @default.
• W1999136737 hasConceptScore W1999136737C45347329 @default.
• W1999136737 hasConceptScore W1999136737C50644808 @default.
• W1999136737 hasConceptScore W1999136737C94915269 @default.
• W1999136737 hasConceptScore W1999136737C99498987 @default.
• W1999136737 hasIssue "21" @default.
• W1999136737 hasLocation W19991367371 @default.
• W1999136737 hasLocation W19991367372 @default.
• W1999136737 hasOpenAccess W1999136737 @default.
• W1999136737 hasPrimaryLocation W19991367371 @default.
• W1999136737 hasRelatedWork W1977194531 @default.
• W1999136737 hasRelatedWork W1980565403 @default.
• W1999136737 hasRelatedWork W1988319384 @default.
• W1999136737 hasRelatedWork W2005382324 @default.
• W1999136737 hasRelatedWork W2038959149 @default.
• W1999136737 hasRelatedWork W2043229322 @default.
• W1999136737 hasRelatedWork W2043921120 @default.

• next