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Journal Abstract Search

796 related items for PubMed ID: 33555354

  • 1. Deep learning reconstruction for contrast-enhanced CT of the upper abdomen: similar image quality with lower radiation dose in direct comparison with iterative reconstruction.
    Nam JG, Hong JH, Kim DS, Oh J, Goo JM.
    Eur Radiol; 2021 Aug; 31(8):5533-5543. PubMed ID: 33555354
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  • 2. Image quality of ultralow-dose chest CT using deep learning techniques: potential superiority of vendor-agnostic post-processing over vendor-specific techniques.
    Nam JG, Ahn C, Choi H, Hong W, Park J, Kim JH, Goo JM.
    Eur Radiol; 2021 Jul; 31(7):5139-5147. PubMed ID: 33415436
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  • 3. Validation of Deep-Learning Image Reconstruction for Low-Dose Chest Computed Tomography Scan: Emphasis on Image Quality and Noise.
    Kim JH, Yoon HJ, Lee E, Kim I, Cha YK, Bak SH.
    Korean J Radiol; 2021 Jan; 22(1):131-138. PubMed ID: 32729277
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  • 4. Image Quality Improvement of Low-dose Abdominal CT using Deep Learning Image Reconstruction Compared with the Second Generation Iterative Reconstruction.
    Kang HJ, Lee JM, Park SJ, Lee SM, Joo I, Yoon JH.
    Curr Med Imaging; 2024 Jan; 20():e250523217310. PubMed ID: 37231764
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  • 8. Improving spatial resolution and diagnostic confidence with thinner slice and deep learning image reconstruction in contrast-enhanced abdominal CT.
    Cao L, Liu X, Qu T, Cheng Y, Li J, Li Y, Chen L, Niu X, Tian Q, Guo J.
    Eur Radiol; 2023 Mar; 33(3):1603-1611. PubMed ID: 36190531
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  • 10. Application of deep learning image reconstruction in low-dose chest CT scan.
    Wang H, Li LL, Shang J, Song J, Liu B.
    Br J Radiol; 2022 May 01; 95(1133):20210380. PubMed ID: 35084210
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  • 11. Can 1.25 mm thin-section images generated with Deep Learning Image Reconstruction technique replace standard-of-care 5 mm images in abdominal CT?
    Cao J, Mroueh N, Pisuchpen N, Parakh A, Lennartz S, Pierce TT, Kambadakone AR.
    Abdom Radiol (NY); 2023 Oct 01; 48(10):3253-3264. PubMed ID: 37369922
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  • 13. Task-based characterization of a deep learning image reconstruction and comparison with filtered back-projection and a partial model-based iterative reconstruction in abdominal CT: A phantom study.
    Racine D, Becce F, Viry A, Monnin P, Thomsen B, Verdun FR, Rotzinger DC.
    Phys Med; 2020 Aug 01; 76():28-37. PubMed ID: 32574999
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  • 17. Improving lesion conspicuity in abdominal dual-energy CT with deep learning image reconstruction: a prospective study with five readers.
    Zhong J, Wang L, Shen H, Li J, Lu W, Shi X, Xing Y, Hu Y, Ge X, Ding D, Yan F, Du L, Yao W, Zhang H.
    Eur Radiol; 2023 Aug 01; 33(8):5331-5343. PubMed ID: 36976337
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  • 18. Assessment of Image Quality of Coronary Computed Tomography Angiography in Obese Patients by Comparing Deep Learning Image Reconstruction With Adaptive Statistical Iterative Reconstruction Veo.
    Wang H, Wang R, Li Y, Zhou Z, Gao Y, Bo K, Yu M, Sun Z, Xu L.
    J Comput Assist Tomogr; 2023 Aug 01; 46(1):34-40. PubMed ID: 35099134
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  • 20. Image Quality Assessment of Abdominal CT by Use of New Deep Learning Image Reconstruction: Initial Experience.
    Jensen CT, Liu X, Tamm EP, Chandler AG, Sun J, Morani AC, Javadi S, Wagner-Bartak NA.
    AJR Am J Roentgenol; 2020 Jul 01; 215(1):50-57. PubMed ID: 32286872
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