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Journal Abstract Search

184 related items for PubMed ID: 34622597

  • 1. [Application of Deep Learning Reconstruction Algorithm in Low-Dose Thin-Slice Liver CT of Healthy Volunteers].
    Zeng LM, Xu X, Zeng W, Peng WL, Zhang JG, Hu SX, Liu KL, Xia CC, Li ZL.
    Sichuan Da Xue Xue Bao Yi Xue Ban; 2021 Sep; 52(5):807-812. PubMed ID: 34622597
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  • 5. Computed tomography of the cervical spine: comparison of image quality between a standard-dose and a low-dose protocol using filtered back-projection and iterative reconstruction.
    Becce F, Ben Salah Y, Verdun FR, Vande Berg BC, Lecouvet FE, Meuli R, Omoumi P.
    Skeletal Radiol; 2013 Jul; 42(7):937-45. PubMed ID: 23359034
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  • 6. Quantitative Image Quality and Histogram-Based Evaluations of an Iterative Reconstruction Algorithm at Low-to-Ultralow Radiation Dose Levels: A Phantom Study in Chest CT.
    Lee KB, Goo HW.
    Korean J Radiol; 2018 Jul; 19(1):119-129. PubMed ID: 29354008
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  • 7. Image Quality and Lesion Detectability of Pancreatic Phase Thin-Slice Computed Tomography Images With a Deep Learning-Based Reconstruction Algorithm.
    Nakamoto A, Onishi H, Tsuboyama T, Fukui H, Ota T, Ogawa K, Yano K, Kiso K, Honda T, Tatsumi M, Tomiyama N.
    J Comput Assist Tomogr; 2018 Jul; 47(5):698-703. PubMed ID: 37707398
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  • 8. The effect of deep learning reconstruction on abdominal CT densitometry and image quality: a systematic review and meta-analysis.
    van Stiphout JA, Driessen J, Koetzier LR, Ruules LB, Willemink MJ, Heemskerk JWT, van der Molen AJ.
    Eur Radiol; 2022 May; 32(5):2921-2929. PubMed ID: 34913104
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  • 10. Impact of iterative reconstruction on CNR and SNR in dynamic myocardial perfusion imaging in an animal model.
    Gramer BM, Muenzel D, Leber V, von Thaden AK, Feussner H, Schneider A, Vembar M, Soni N, Rummeny EJ, Huber AM.
    Eur Radiol; 2012 Dec; 22(12):2654-61. PubMed ID: 22752461
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  • 11. Chest CT with iterative reconstruction algorithms for airway stent evaluation in patients with malignant obstructive tracheobronchial diseases.
    Li T, Zhang Y, Wang Y, Gao J, Jiang Y.
    Medicine (Baltimore); 2016 Sep; 95(39):e4873. PubMed ID: 27684818
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  • 13. Ultra-low peak voltage CT colonography: effect of iterative reconstruction algorithms on performance of radiologists who use anthropomorphic colonic phantoms.
    Shin CI, Kim SH, Lee ES, Lee DH, Hwang EJ, Chung SY, Lee JM, Han JK, Choi BI.
    Radiology; 2014 Dec; 273(3):759-71. PubMed ID: 25010640
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  • 14. Noise and spatial resolution properties of a commercially available deep learning-based CT reconstruction algorithm.
    Solomon J, Lyu P, Marin D, Samei E.
    Med Phys; 2020 Sep; 47(9):3961-3971. PubMed ID: 32506661
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  • 15. Improvement in Image Quality and Visibility of Coronary Arteries, Stents, and Valve Structures on CT Angiography by Deep Learning Reconstruction.
    Otgonbaatar C, Ryu JK, Shin J, Woo JY, Seo JW, Shim H, Hwang DH.
    Korean J Radiol; 2022 Nov; 23(11):1044-1054. PubMed ID: 36196766
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  • 16. [Noise Reduction Effect of Deep-learning-based Image Reconstruction Algorithms in Thin-section Chest CT].
    Zeng W, Zeng LM, Xu X, Hu SX, Liu KL, Zhang JG, Peng WL, Xia CC, Li ZL.
    Sichuan Da Xue Xue Bao Yi Xue Ban; 2021 Mar; 52(2):286-292. PubMed ID: 33829704
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  • 17. Computed Tomography Effective Dose and Image Quality in Deep Learning Image Reconstruction in Intensive Care Patients Compared to Iterative Algorithms.
    Quaia E, Kiyomi Lanza de Cristoforis E, Agostini E, Zanon C.
    Tomography; 2024 Jun 07; 10(6):912-921. PubMed ID: 38921946
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  • 18. Low-dose whole-body CT using deep learning image reconstruction: image quality and lesion detection.
    Noda Y, Kaga T, Kawai N, Miyoshi T, Kawada H, Hyodo F, Kambadakone A, Matsuo M.
    Br J Radiol; 2021 May 01; 94(1121):20201329. PubMed ID: 33571010
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  • 20. Contrast-Enhanced CT with Knowledge-Based Iterative Model Reconstruction for the Evaluation of Parotid Gland Tumors: A Feasibility Study.
    Park CJ, Kim KW, Lee HJ, Kim MJ, Kim J.
    Korean J Radiol; 2018 May 01; 19(5):957-964. PubMed ID: 30174486
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