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Journal Abstract Search

857 related items for PubMed ID: 32090528

  • 1. Low-Dose Abdominal CT Using a Deep Learning-Based Denoising Algorithm: A Comparison with CT Reconstructed with Filtered Back Projection or Iterative Reconstruction Algorithm.
    Shin YJ, Chang W, Ye JC, Kang E, Oh DY, Lee YJ, Park JH, Kim YH.
    Korean J Radiol; 2020 Mar; 21(3):356-364. PubMed ID: 32090528
    [Abstract] [Full Text] [Related]

  • 2. Deep learning-based denoising algorithm in comparison to iterative reconstruction and filtered back projection: a 12-reader phantom study.
    Kim Y, Oh DY, Chang W, Kang E, Ye JC, Lee K, Kim HY, Kim YH, Park JH, Lee YJ, Lee KH.
    Eur Radiol; 2021 Nov; 31(11):8755-8764. PubMed ID: 33885958
    [Abstract] [Full Text] [Related]

  • 3. Image Quality and Lesion Detection on Deep Learning Reconstruction and Iterative Reconstruction of Submillisievert Chest and Abdominal CT.
    Singh R, Digumarthy SR, Muse VV, Kambadakone AR, Blake MA, Tabari A, Hoi Y, Akino N, Angel E, Madan R, Kalra MK.
    AJR Am J Roentgenol; 2020 Mar; 214(3):566-573. PubMed ID: 31967501
    [Abstract] [Full Text] [Related]

  • 4. 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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  • 7. Image quality evaluation in deep-learning-based CT noise reduction using virtual imaging trial methods: Contrast-dependent spatial resolution.
    Zhou Z, Gong H, Hsieh S, McCollough CH, Yu L.
    Med Phys; 2024 Aug; 51(8):5399-5413. PubMed ID: 38555876
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  • 8. Ultra-low dose abdominal MDCT: using a knowledge-based Iterative Model Reconstruction technique for substantial dose reduction in a prospective clinical study.
    Khawaja RDA, Singh S, Blake M, Harisinghani M, Choy G, Karosmangulu A, Padole A, Do S, Brown K, Thompson R, Morton T, Raihani N, Koehler T, Kalra MK.
    Eur J Radiol; 2015 Jan; 84(1):2-10. PubMed ID: 25458225
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  • 10. Reaching for better image quality and lower radiation dose in head and neck CT: advanced modeled and sinogram-affirmed iterative reconstruction in combination with tube voltage adaptation.
    Schmid AI, Uder M, Lell MM.
    Dentomaxillofac Radiol; 2017 Jan; 46(1):20160131. PubMed ID: 27540625
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  • 12. Performance of adaptive iterative dose reduction 3D integrated with automatic tube current modulation in radiation dose and image noise reduction compared with filtered-back projection for 80-kVp abdominal CT: Anthropomorphic phantom and patient study.
    Chen CM, Lin YY, Hsu MY, Hung CF, Liao YL, Tsai HY.
    Eur J Radiol; 2016 Sep; 85(9):1666-72. PubMed ID: 27501904
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  • 13. Assessment of a model-based, iterative reconstruction algorithm (MBIR) regarding image quality and dose reduction in liver computed tomography.
    Chang W, Lee JM, Lee K, Yoon JH, Yu MH, Han JK, Choi BI.
    Invest Radiol; 2013 Aug; 48(8):598-606. PubMed ID: 23511193
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  • 14. 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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  • 16. Knowledge-based iterative model reconstruction (IMR) algorithm in ultralow-dose CT for evaluation of urolithiasis: evaluation of radiation dose reduction, image quality, and diagnostic performance.
    Park SB, Kim YS, Lee JB, Park HJ.
    Abdom Imaging; 2015 Oct 07; 40(8):3137-46. PubMed ID: 26197735
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  • 18. [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 07; 52(5):807-812. PubMed ID: 34622597
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  • 19. Characteristic image quality of a third generation dual-source MDCT scanner: Noise, resolution, and detectability.
    Solomon J, Wilson J, Samei E.
    Med Phys; 2015 Aug 07; 42(8):4941-53. PubMed ID: 26233220
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