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Journal Abstract Search

198 related items for PubMed ID: 31063429

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  • 2. Effect of slab thickness on the CT detection of pulmonary nodules: use of sliding thin-slab maximum intensity projection and volume rendering.
    Kawel N, Seifert B, Luetolf M, Boehm T.
    AJR Am J Roentgenol; 2009 May; 192(5):1324-9. PubMed ID: 19380557
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  • 5. Comparison of the effects of model-based iterative reconstruction and filtered back projection algorithms on software measurements in pulmonary subsolid nodules.
    Cohen JG, Kim H, Park SB, van Ginneken B, Ferretti GR, Lee CH, Goo JM, Park CM.
    Eur Radiol; 2017 Aug; 27(8):3266-3274. PubMed ID: 28058482
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  • 8. Deep learning-based pulmonary nodule detection: Effect of slab thickness in maximum intensity projections at the nodule candidate detection stage.
    Zheng S, Cui X, Vonder M, Veldhuis RNJ, Ye Z, Vliegenthart R, Oudkerk M, van Ooijen PMA.
    Comput Methods Programs Biomed; 2020 Nov; 196():105620. PubMed ID: 32615493
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  • 9. Malignancy estimation of Lung-RADS criteria for subsolid nodules on CT: accuracy of low and high risk spectrum when using NLST nodules.
    Chung K, Jacobs C, Scholten ET, Mets OM, Dekker I, Prokop M, van Ginneken B, Schaefer-Prokop CM.
    Eur Radiol; 2017 Nov; 27(11):4672-4679. PubMed ID: 28439653
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  • 10. Benefit of computer-aided detection analysis for the detection of subsolid and solid lung nodules on thin- and thick-section CT.
    Godoy MC, Kim TJ, White CS, Bogoni L, de Groot P, Florin C, Obuchowski N, Babb JS, Salganicoff M, Naidich DP, Anand V, Park S, Vlahos I, Ko JP.
    AJR Am J Roentgenol; 2013 Jan; 200(1):74-83. PubMed ID: 23255744
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  • 12. Sub-solid Nodule Detection Performance on Reduced-dose Computed Tomography with Iterative Reduction: Comparison Between 20 mA (7 mAs) and 120 mA (42 mAs) Regarding Nodular Size and Characteristics and Association with Size-specific Dose Estimate.
    Nagatani Y, Takahashi M, Ikeda M, Yamashiro T, Koyama H, Koyama M, Moriya H, Noma S, Tomiyama N, Ohno Y, Murata K, Murayama S, investigators of ACTIve study group.
    Acad Radiol; 2017 Aug; 24(8):995-1007. PubMed ID: 28606593
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  • 13. Whole-Lesion Computed Tomography-Based Entropy Parameters for the Differentiation of Minimally Invasive and Invasive Adenocarcinomas Appearing as Pulmonary Subsolid Nodules.
    Chen X, Feng B, Chen Y, Hao Y, Duan X, Cui E, Liu Z, Zhang C, Long W.
    J Comput Assist Tomogr; 2019 Aug; 43(5):817-824. PubMed ID: 31343995
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  • 16. Performance of ultralow-dose CT with iterative reconstruction in lung cancer screening: limiting radiation exposure to the equivalent of conventional chest X-ray imaging.
    Huber A, Landau J, Ebner L, Bütikofer Y, Leidolt L, Brela B, May M, Heverhagen J, Christe A.
    Eur Radiol; 2016 Oct; 26(10):3643-52. PubMed ID: 26813670
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  • 20. Detection of Subsolid Nodules in Lung Cancer Screening: Complementary Sensitivity of Visual Reading and Computer-Aided Diagnosis.
    Silva M, Schaefer-Prokop CM, Jacobs C, Capretti G, Ciompi F, van Ginneken B, Pastorino U, Sverzellati N.
    Invest Radiol; 2018 Aug; 53(8):441-449. PubMed ID: 29543693
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