Matches in SemOpenAlex for { <https://semopenalex.org/work/W4287828101> ?p ?o ?g. }
Showing items 1 to 59 of
59
with 100 items per page.
- W4287828101 abstract "Spectral Photon-Counting Computed Tomography (SPCCT) is a promising technology that has shown a number of advantages over conventional X-ray Computed Tomography (CT) in the form of material separation, artefact removal and enhanced image quality. However, due to the increased complexity and non-linearity of the SPCCT governing equations, model-based reconstruction algorithms typically require handcrafted regularisation terms and meticulous tuning of hyperparameters making them impractical to calibrate in variable conditions. Additionally, they typically incur high computational costs and in cases of limited-angle data, their imaging capability deteriorates significantly. Recently, Deep Learning has proven to provide state-of-the-art reconstruction performance in medical imaging applications while circumventing most of these challenges. Inspired by these advances, we propose a Deep Learning imaging method for SPCCT that exploits the expressive power of Neural Networks while also incorporating model knowledge. The method takes the form of a two-step learned primal-dual algorithm that is trained using case-specific data. The proposed approach is characterised by fast reconstruction capability and high imaging performance, even in limited-data cases, while avoiding the hand-tuning that is required by other optimisation approaches. We demonstrate the performance of the method in terms of reconstructed images and quality metrics via numerical examples inspired by the application of cardiovascular imaging." @default.
- W4287828101 created "2022-07-26" @default.
- W4287828101 creator A5003880635 @default.
- W4287828101 creator A5051687116 @default.
- W4287828101 creator A5085998023 @default.
- W4287828101 date "2020-03-09" @default.
- W4287828101 modified "2023-09-26" @default.
- W4287828101 title "Learned Spectral Computed Tomography" @default.
- W4287828101 doi "https://doi.org/10.48550/arxiv.2003.04138" @default.
- W4287828101 hasPublicationYear "2020" @default.
- W4287828101 type Work @default.
- W4287828101 citedByCount "0" @default.
- W4287828101 crossrefType "posted-content" @default.
- W4287828101 hasAuthorship W4287828101A5003880635 @default.
- W4287828101 hasAuthorship W4287828101A5051687116 @default.
- W4287828101 hasAuthorship W4287828101A5085998023 @default.
- W4287828101 hasBestOaLocation W42878281011 @default.
- W4287828101 hasConcept C108583219 @default.
- W4287828101 hasConcept C11413529 @default.
- W4287828101 hasConcept C119857082 @default.
- W4287828101 hasConcept C126838900 @default.
- W4287828101 hasConcept C141379421 @default.
- W4287828101 hasConcept C154945302 @default.
- W4287828101 hasConcept C165696696 @default.
- W4287828101 hasConcept C31601959 @default.
- W4287828101 hasConcept C38652104 @default.
- W4287828101 hasConcept C41008148 @default.
- W4287828101 hasConcept C544519230 @default.
- W4287828101 hasConcept C71924100 @default.
- W4287828101 hasConcept C8642999 @default.
- W4287828101 hasConceptScore W4287828101C108583219 @default.
- W4287828101 hasConceptScore W4287828101C11413529 @default.
- W4287828101 hasConceptScore W4287828101C119857082 @default.
- W4287828101 hasConceptScore W4287828101C126838900 @default.
- W4287828101 hasConceptScore W4287828101C141379421 @default.
- W4287828101 hasConceptScore W4287828101C154945302 @default.
- W4287828101 hasConceptScore W4287828101C165696696 @default.
- W4287828101 hasConceptScore W4287828101C31601959 @default.
- W4287828101 hasConceptScore W4287828101C38652104 @default.
- W4287828101 hasConceptScore W4287828101C41008148 @default.
- W4287828101 hasConceptScore W4287828101C544519230 @default.
- W4287828101 hasConceptScore W4287828101C71924100 @default.
- W4287828101 hasConceptScore W4287828101C8642999 @default.
- W4287828101 hasLocation W42878281011 @default.
- W4287828101 hasOpenAccess W4287828101 @default.
- W4287828101 hasPrimaryLocation W42878281011 @default.
- W4287828101 hasRelatedWork W2908875379 @default.
- W4287828101 hasRelatedWork W3047644063 @default.
- W4287828101 hasRelatedWork W3123344745 @default.
- W4287828101 hasRelatedWork W3196786996 @default.
- W4287828101 hasRelatedWork W4210794429 @default.
- W4287828101 hasRelatedWork W4223943233 @default.
- W4287828101 hasRelatedWork W4280644903 @default.
- W4287828101 hasRelatedWork W4281616679 @default.
- W4287828101 hasRelatedWork W4281780675 @default.
- W4287828101 hasRelatedWork W4283697347 @default.
- W4287828101 isParatext "false" @default.
- W4287828101 isRetracted "false" @default.
- W4287828101 workType "article" @default.