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Kunio Doi to Lung

This is a "connection" page, showing publications Kunio Doi has written about Lung.

 
Connection Strength
 
 
 
2.388
 
  1. Suzuki K, Doi K. How can a massive training artificial neural network (MTANN) be trained with a small number of cases in the distinction between nodules and vessels in thoracic CT? Acad Radiol. 2005 Oct; 12(10):1333-41.
    View in: PubMed
    Score: 0.187
  2. Woo GH, Bak EJ, Nakayama H, Doi K. Hydroxyurea (HU)-induced apoptosis in the mouse fetal lung. Exp Mol Pathol. 2005 Aug; 79(1):59-67.
    View in: PubMed
    Score: 0.182
  3. Ohtsuka R, Shutoh Y, Fujie H, Yamaguchi S, Takeda M, Harada T, Doi K. Changes in histology and expression of cytokines and chemokines in the rat lung following exposure to ovalbumin. Exp Toxicol Pathol. 2005 Apr; 56(6):361-8.
    View in: PubMed
    Score: 0.181
  4. Kakeda S, Moriya J, Sato H, Aoki T, Watanabe H, Nakata H, Oda N, Katsuragawa S, Yamamoto K, Doi K. Improved detection of lung nodules on chest radiographs using a commercial computer-aided diagnosis system. AJR Am J Roentgenol. 2004 Feb; 182(2):505-10.
    View in: PubMed
    Score: 0.167
  5. Li Q, Sone S, Doi K. Selective enhancement filters for nodules, vessels, and airway walls in two- and three-dimensional CT scans. Med Phys. 2003 Aug; 30(8):2040-51.
    View in: PubMed
    Score: 0.161
  6. Li F, Sone S, Abe H, MacMahon H, Armato SG, Doi K. Lung cancers missed at low-dose helical CT screening in a general population: comparison of clinical, histopathologic, and imaging findings. Radiology. 2002 Dec; 225(3):673-83.
    View in: PubMed
    Score: 0.154
  7. Masutani Y, MacMahon H, Doi K. Automated segmentation and visualization of the pulmonary vascular tree in spiral CT angiography: an anatomy-oriented approach based on three-dimensional image analysis. J Comput Assist Tomogr. 2001 Jul-Aug; 25(4):587-97.
    View in: PubMed
    Score: 0.139
  8. Monnier-Cholley L, MacMahon H, Katsuragawa S, Morishita J, Ishida T, Doi K. Computer-aided diagnosis for detection of interstitial opacities on chest radiographs. AJR Am J Roentgenol. 1998 Dec; 171(6):1651-6.
    View in: PubMed
    Score: 0.117
  9. Xu XW, Doi K. Image feature analysis for computer-aided diagnosis: detection of right and left hemidiaphragm edges and delineation of lung field in chest radiographs. Med Phys. 1996 Sep; 23(9):1613-24.
    View in: PubMed
    Score: 0.100
  10. Monnier-Cholley L, MacMahon H, Katsuragawa S, Morishita J, Doi K. Computerized analysis of interstitial infiltrates on chest radiographs: a new scheme based on geometric pattern features and Fourier analysis. Acad Radiol. 1995 Jun; 2(6):455-62.
    View in: PubMed
    Score: 0.091
  11. Xu XW, Doi K. Image feature analysis for computer-aided diagnosis: accurate determination of ribcage boundary in chest radiographs. Med Phys. 1995 May; 22(5):617-26.
    View in: PubMed
    Score: 0.091
  12. Doi K. [Science of similar images: quantitative evaluation on the similarity of images to be used in the next generation CAD]. Nihon Hoshasen Gijutsu Gakkai Zasshi. 2011; 67(4):400-12.
    View in: PubMed
    Score: 0.067
  13. Lam KL, Chan HP, MacMahon H, Oravecz WT, Doi K. Dynamic digital subtraction evaluation of regional pulmonary ventilation with nonradioactive xenon. Invest Radiol. 1990 Jun; 25(6):728-35.
    View in: PubMed
    Score: 0.065
  14. Nie Y, Li Q, Li F, Pu Y, Appelbaum D, Doi K. Integrating PET and CT information to improve diagnostic accuracy for lung nodules: A semiautomatic computer-aided method. J Nucl Med. 2006 Jul; 47(7):1075-80.
    View in: PubMed
    Score: 0.049
  15. Shiraishi J, Li Q, Suzuki K, Engelmann R, Doi K. Computer-aided diagnostic scheme for the detection of lung nodules on chest radiographs: localized search method based on anatomical classification. Med Phys. 2006 Jul; 33(7):2642-53.
    View in: PubMed
    Score: 0.049
  16. Suzuki K, Shiraishi J, Abe H, MacMahon H, Doi K. False-positive reduction in computer-aided diagnostic scheme for detecting nodules in chest radiographs by means of massive training artificial neural network. Acad Radiol. 2005 Feb; 12(2):191-201.
    View in: PubMed
    Score: 0.045
  17. Li F, Aoyama M, Shiraishi J, Abe H, Li Q, Suzuki K, Engelmann R, Sone S, Macmahon H, Doi K. Radiologists' performance for differentiating benign from malignant lung nodules on high-resolution CT using computer-estimated likelihood of malignancy. AJR Am J Roentgenol. 2004 Nov; 183(5):1209-15.
    View in: PubMed
    Score: 0.044
  18. Li Q, Li F, Shiraishi J, Katsuragawa S, Sone S, Doi K. Investigation of new psychophysical measures for evaluation of similar images on thoracic computed tomography for distinction between benign and malignant nodules. Med Phys. 2003 Oct; 30(10):2584-93.
    View in: PubMed
    Score: 0.041
  19. Uchiyama Y, Katsuragawa S, Abe H, Shiraishi J, Li F, Li Q, Zhang CT, Suzuki K, Doi K. Quantitative computerized analysis of diffuse lung disease in high-resolution computed tomography. Med Phys. 2003 Sep; 30(9):2440-54.
    View in: PubMed
    Score: 0.041
  20. Suzuki K, Armato SG, Li F, Sone S, Doi K. Massive training artificial neural network (MTANN) for reduction of false positives in computerized detection of lung nodules in low-dose computed tomography. Med Phys. 2003 Jul; 30(7):1602-17.
    View in: PubMed
    Score: 0.040
  21. Adachi K, Suzuki M, Sugimoto T, Uetsuka K, Nakamaya H, Doi K. Effects of granulocyte colony-stimulating factor on the kinetics of inflammatory cells in the peripheral blood and pulmonary lesions during the development of bleomycin-induced lung injury in rats. Exp Toxicol Pathol. 2003 Jul; 55(1):21-32.
    View in: PubMed
    Score: 0.040
  22. Adach K, Suzuki M, Sugimoto T, Suzuki S, Niki R, Oyama A, Uetsuka K, Nakamaya H, Doi K. Granulocyte colony-stimulating factor exacerbates the acute lung injury and pulmonary fibrosis induced by intratracheal administration of bleomycin in rats. Exp Toxicol Pathol. 2002 Feb; 53(6):501-10.
    View in: PubMed
    Score: 0.036
  23. Li Q, Katsuragawa S, Doi K. Improved contralateral subtraction images by use of elastic matching technique. Med Phys. 2000 Aug; 27(8):1934-42.
    View in: PubMed
    Score: 0.033
  24. Nakamura K, Yoshida H, Engelmann R, MacMahon H, Katsuragawa S, Ishida T, Ashizawa K, Doi K. Computerized analysis of the likelihood of malignancy in solitary pulmonary nodules with use of artificial neural networks. Radiology. 2000 Mar; 214(3):823-30.
    View in: PubMed
    Score: 0.032
  25. Armato SG, Giger ML, Moran CJ, Blackburn JT, Doi K, MacMahon H. Computerized detection of pulmonary nodules on CT scans. Radiographics. 1999 Sep-Oct; 19(5):1303-11.
    View in: PubMed
    Score: 0.031
  26. Ishida T, Katsuragawa S, Nakamura K, MacMahon H, Doi K. Iterative image warping technique for temporal subtraction of sequential chest radiographs to detect interval change. Med Phys. 1999 Jul; 26(7):1320-9.
    View in: PubMed
    Score: 0.030
  27. Ishida T, Ashizawa K, Engelmann R, Katsuragawa S, MacMahon H, Doi K. Application of temporal subtraction for detection of interval changes on chest radiographs: improvement of subtraction images using automated initial image matching. J Digit Imaging. 1999 May; 12(2):77-86.
    View in: PubMed
    Score: 0.030
  28. Katsuragawa S, Doi K, MacMahon H, Monnier-Cholley L, Ishida T, Kobayashi T. Classification of normal and abnormal lungs with interstitial diseases by rule-based method and artificial neural networks. J Digit Imaging. 1997 Aug; 10(3):108-14.
    View in: PubMed
    Score: 0.027
  29. Matsumoto T, Yoshimura H, Doi K, Giger ML, Kano A, MacMahon H, Abe K, Montner SM. Image feature analysis of false-positive diagnoses produced by automated detection of lung nodules. Invest Radiol. 1992 Aug; 27(8):587-97.
    View in: PubMed
    Score: 0.019
  30. Katsuragawa S, Doi K, MacMahon H, Nakamori N, Sasaki Y, Fennessy JJ. Quantitative computer-aided analysis of lung texture in chest radiographs. Radiographics. 1990 Mar; 10(2):257-69.
    View in: PubMed
    Score: 0.016
  31. Katsuragawa S, Doi K, MacMahon H. Image feature analysis and computer-aided diagnosis in digital radiography: classification of normal and abnormal lungs with interstitial disease in chest images. Med Phys. 1989 Jan-Feb; 16(1):38-44.
    View in: PubMed
    Score: 0.015
  32. Powell GF, Doi K, Katsuragawa S. Localization of inter-rib spaces for lung texture analysis and computer-aided diagnosis in digital chest images. Med Phys. 1988 Jul-Aug; 15(4):581-7.
    View in: PubMed
    Score: 0.014
  33. Giger ML, Doi K, MacMahon H. Image feature analysis and computer-aided diagnosis in digital radiography. 3. Automated detection of nodules in peripheral lung fields. Med Phys. 1988 Mar-Apr; 15(2):158-66.
    View in: PubMed
    Score: 0.014
  34. MacMahon H, Vyborny CJ, Metz CE, Doi K, Sabeti V, Solomon SL. Digital radiography of subtle pulmonary abnormalities: an ROC study of the effect of pixel size on observer performance. Radiology. 1986 Jan; 158(1):21-6.
    View in: PubMed
    Score: 0.012
  35. Doi K, Maeda N, Doi C, Isegawa N, Sugano S, Mitsuoka T. Distribution and incidence of calcified lesions in DBA/2NCrj and BALB/cAnNCrj mice. Nihon Juigaku Zasshi. 1985 Jun; 47(3):479-82.
    View in: PubMed
    Score: 0.011
  36. Ohtsuka R, Doi K, Itagaki S. Histological characteristics of respiratory system in Brown Norway rat. Exp Anim. 1997 Apr; 46(2):127-33.
    View in: PubMed
    Score: 0.006
  37. Yoshimura H, Giger ML, Doi K, MacMahon H, Montner SM. Computerized scheme for the detection of pulmonary nodules. A nonlinear filtering technique. Invest Radiol. 1992 Feb; 27(2):124-9.
    View in: PubMed
    Score: 0.005
  38. Sanada S, Doi K, MacMahon H. Image feature analysis and computer-aided diagnosis in digital radiography: automated delineation of posterior ribs in chest images. Med Phys. 1991 Sep-Oct; 18(5):964-71.
    View in: PubMed
    Score: 0.004
  39. Nakamori N, Doi K, Sabeti V, MacMahon H. Image feature analysis and computer-aided diagnosis in digital radiography: automated analysis of sizes of heart and lung in chest images. Med Phys. 1990 May-Jun; 17(3):342-50.
    View in: PubMed
    Score: 0.004
Connection Strength

The connection strength for concepts is the sum of the scores for each matching publication.

Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.