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Journal Abstract Search

312 related items for PubMed ID: 14528966

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  • 5. Feasibility of automated quantification of regional disease patterns depicted on high-resolution computed tomography in patients with various diffuse lung diseases.
    Park SO, Seo JB, Kim N, Park SH, Lee YK, Park BW, Sung YS, Lee Y, Lee J, Kang SH.
    Korean J Radiol; 2009; 10(5):455-63. PubMed ID: 19721830
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  • 7. A support vector machine classifier reduces interscanner variation in the HRCT classification of regional disease pattern in diffuse lung disease: comparison to a Bayesian classifier.
    Chang Y, Lim J, Kim N, Seo JB, Lynch DA.
    Med Phys; 2013 May; 40(5):051912. PubMed ID: 23635282
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  • 8. High resolution multidetector CT-aided tissue analysis and quantification of lung fibrosis.
    Zavaletta VA, Bartholmai BJ, Robb RA.
    Acad Radiol; 2007 Jul; 14(7):772-87. PubMed ID: 17574128
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  • 9. Multiple kernel learning for classification of diffuse lung disease using HRCT lung images.
    Vo KT, Sowmya A.
    Annu Int Conf IEEE Eng Med Biol Soc; 2010 Jul; 2010():3085-8. PubMed ID: 21095740
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  • 10. [High-resolution volumetric computerized tomography of the lung: optimization of technique and image quality as a function of its clinical-diagnostic use and dose to the patient].
    Gavelli G, Giampalma E, Cenni M, Pierotti L, Cavina M, Bergamini C.
    Radiol Med; 1998 Apr; 95(4):322-8. PubMed ID: 9676210
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  • 11. Computer-aided diagnostic scheme for the detection of lung nodules on chest radiographs: localized search method based on anatomical classification.
    Shiraishi J, Li Q, Suzuki K, Engelmann R, Doi K.
    Med Phys; 2006 Jul; 33(7):2642-53. PubMed ID: 16898468
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  • 12. Knowledge-driven automated detection of pleural plaques and thickening in high resolution CT of the lung.
    Rudrapatna M, Mai V, Sowmya A, Wilson P.
    Inf Process Med Imaging; 2005 Jul; 19():270-85. PubMed ID: 17354702
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  • 13. Radiologists' performance for differentiating benign from malignant lung nodules on high-resolution CT using computer-estimated likelihood of malignancy.
    Li F, Aoyama M, Shiraishi J, Abe H, Li Q, Suzuki K, Engelmann R, Sone S, Macmahon H, Doi K.
    AJR Am J Roentgenol; 2004 Nov; 183(5):1209-15. PubMed ID: 15505279
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  • 14. Computerized scheme for automated detection of lung nodules in low-dose computed tomography images for lung cancer screening.
    Arimura H, Katsuragawa S, Suzuki K, Li F, Shiraishi J, Sone S, Doi K.
    Acad Radiol; 2004 Jun; 11(6):617-29. PubMed ID: 15172364
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  • 16. High-resolution computed tomography patterns of diffuse interstitial lung disease with clinical and pathological correlation.
    Elicker B, Pereira CA, Webb R, Leslie KO.
    J Bras Pneumol; 2008 Sep; 34(9):715-44. PubMed ID: 18982210
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  • 17. Application of an artificial neural network to high-resolution CT: usefulness in differential diagnosis of diffuse lung disease.
    Fukushima A, Ashizawa K, Yamaguchi T, Matsuyama N, Hayashi H, Kida I, Imafuku Y, Egawa A, Kimura S, Nagaoki K, Honda S, Katsuragawa S, Doi K, Hayashi K.
    AJR Am J Roentgenol; 2004 Aug; 183(2):297-305. PubMed ID: 15269016
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  • 20. Automatic detection and quantification of ground-glass opacities on high-resolution CT using multiple neural networks: comparison with a density mask.
    Kauczor HU, Heitmann K, Heussel CP, Marwede D, Uthmann T, Thelen M.
    AJR Am J Roentgenol; 2000 Nov; 175(5):1329-34. PubMed ID: 11044035
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