FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4281609905> ?p ?o ?g. }

• W4281609905 endingPage "5561" @default.
• W4281609905 startingPage "5545" @default.
• W4281609905 abstract "Abstract Conventional reconstruction techniques, such as filtered back projection (FBP) and iterative reconstruction (IR), which have been utilised widely in the image reconstruction process of computed tomography (CT) are not suitable in the case of low-dose CT applications, because of the unsatisfying quality of the reconstructed image and inefficient reconstruction time. Therefore, as the demand for CT radiation dose reduction continues to increase, the use of artificial intelligence (AI) in image reconstruction has become a trend that attracts more and more attention. This systematic review examined various deep learning methods to determine their characteristics, availability, intended use and expected outputs concerning low-dose CT image reconstruction. Utilising the methodology of Kitchenham and Charter, we performed a systematic search of the literature from 2016 to 2021 in Springer, Science Direct, arXiv, PubMed, ACM, IEEE, and Scopus. This review showed that algorithms using deep learning technology are superior to traditional IR methods in noise suppression, artifact reduction and structure preservation, in terms of improving the image quality of low-dose reconstructed images. In conclusion, we provided an overview of the use of deep learning approaches in low-dose CT image reconstruction together with their benefits, limitations, and opportunities for improvement." @default.
• W4281609905 created "2022-06-12" @default.
• W4281609905 creator A5000919145 @default.
• W4281609905 creator A5019125862 @default.
• W4281609905 creator A5075728961 @default.
• W4281609905 date "2022-05-28" @default.
• W4281609905 modified "2023-10-01" @default.
• W4281609905 title "The use of deep learning methods in low-dose computed tomography image reconstruction: a systematic review" @default.
• W4281609905 cites W2567331605 @default.
• W4281609905 cites W2570202822 @default.
• W4281609905 cites W2584483805 @default.
• W4281609905 cites W2587985573 @default.
• W4281609905 cites W2593226005 @default.
• W4281609905 cites W2611467245 @default.
• W4281609905 cites W2613155248 @default.
• W4281609905 cites W2743780012 @default.
• W4281609905 cites W2748739903 @default.
• W4281609905 cites W2756258573 @default.
• W4281609905 cites W2765479697 @default.
• W4281609905 cites W2766642650 @default.
• W4281609905 cites W2779349455 @default.
• W4281609905 cites W2781681626 @default.
• W4281609905 cites W2789467431 @default.
• W4281609905 cites W2789658131 @default.
• W4281609905 cites W2790610432 @default.
• W4281609905 cites W2791154958 @default.
• W4281609905 cites W2791923256 @default.
• W4281609905 cites W2792273027 @default.
• W4281609905 cites W2793419304 @default.
• W4281609905 cites W2795777276 @default.
• W4281609905 cites W2796256498 @default.
• W4281609905 cites W2801560365 @default.
• W4281609905 cites W2802021665 @default.
• W4281609905 cites W2802168062 @default.
• W4281609905 cites W2805815341 @default.
• W4281609905 cites W2807371744 @default.
• W4281609905 cites W2809226111 @default.
• W4281609905 cites W2889470718 @default.
• W4281609905 cites W2890387689 @default.
• W4281609905 cites W2893497937 @default.
• W4281609905 cites W2898099302 @default.
• W4281609905 cites W2902508714 @default.
• W4281609905 cites W2902719825 @default.
• W4281609905 cites W2905525600 @default.
• W4281609905 cites W2909633804 @default.
• W4281609905 cites W2911459672 @default.
• W4281609905 cites W2913929186 @default.
• W4281609905 cites W2914498953 @default.
• W4281609905 cites W2918549271 @default.
• W4281609905 cites W2919838857 @default.
• W4281609905 cites W2920911464 @default.
• W4281609905 cites W2922913524 @default.
• W4281609905 cites W2930377639 @default.
• W4281609905 cites W2936378778 @default.
• W4281609905 cites W2936895602 @default.
• W4281609905 cites W2938296211 @default.
• W4281609905 cites W2939794740 @default.
• W4281609905 cites W2942039563 @default.
• W4281609905 cites W2945352494 @default.
• W4281609905 cites W2946049212 @default.
• W4281609905 cites W2946539594 @default.
• W4281609905 cites W2947535173 @default.
• W4281609905 cites W2947746588 @default.
• W4281609905 cites W2949693510 @default.
• W4281609905 cites W2953594885 @default.
• W4281609905 cites W2954782146 @default.
• W4281609905 cites W2959456510 @default.
• W4281609905 cites W2962162024 @default.
• W4281609905 cites W2962976869 @default.
• W4281609905 cites W2963392702 @default.
• W4281609905 cites W2963754379 @default.
• W4281609905 cites W2964327615 @default.
• W4281609905 cites W2965401993 @default.
• W4281609905 cites W2970437588 @default.
• W4281609905 cites W2971204923 @default.
• W4281609905 cites W2971916332 @default.
• W4281609905 cites W2972005899 @default.
• W4281609905 cites W2972261808 @default.
• W4281609905 cites W2972922788 @default.
• W4281609905 cites W2977890283 @default.
• W4281609905 cites W2980780523 @default.
• W4281609905 cites W2981735661 @default.
• W4281609905 cites W2982303615 @default.
• W4281609905 cites W2982347932 @default.
• W4281609905 cites W2985267475 @default.
• W4281609905 cites W2992095291 @default.
• W4281609905 cites W2994402878 @default.
• W4281609905 cites W2994431743 @default.
• W4281609905 cites W2994738434 @default.
• W4281609905 cites W2995610300 @default.
• W4281609905 cites W2997151107 @default.
• W4281609905 cites W2997375529 @default.
• W4281609905 cites W2997704384 @default.
• W4281609905 cites W2998251473 @default.
• W4281609905 cites W2998785217 @default.
• W4281609905 cites W2999575735 @default.
• W4281609905 cites W3000953045 @default.
• W4281609905 cites W3003776066 @default.

• next