European Journal of Radiology
Volume 72, Issue 2 , Pages 218-225 , November 2009

Computer-aided detection (CAD) of lung nodules and small tumours on chest radiographs

  • D.W. De Boo

      Affiliations

    • Academic Medical Center (AMC), Dept of Radiology, Meibergdreef 9, 1105 AZ Amsterdam, Netherlands
    • Corresponding Author InformationCorresponding author.
    • ,
  • M. Prokop

      Affiliations

    • University Medical Center (UMC) Utrecht, Dept. of Radiology, Heidelberglaan 100, 3584 CX Utrecht, Netherlands
    • ,
  • M. Uffmann

      Affiliations

    • University Hospital Vienna (AKH) Vienna, Dept. of Radiology, Waehringer Guertel 18-20, 1090 Vienna, Austria
    • ,
  • B. van Ginneken

      Affiliations

    • University Medical Center (UMC) Utrecht, Image Science Center, Heidelberglaan 100, 3584 CX Utrecht, Netherlands
    • ,
  • C.M. Schaefer-Prokop

      Affiliations

    • Academic Medical Center (AMC), Dept of Radiology, Meibergdreef 9, 1105 AZ Amsterdam, Netherlands
    • Meander Medical Center, Dept of Radiology, Utrechtseweg 160, 3800 BM Amersfoort, Netherlands

Received 7 May 2009 ,Accepted 7 May 2009.

References 

  1. Henschke CI, McCauley DI, Yankelevitz DF, et al. Early lung cancer action project: overall design and findings from baseline screening. The Lancet. 1999;354:99–105
  2. Swensen SJ, Jett JR, Hartmann TE, et al. CT screening for lung cancer: five year prospective experience. Radiology. 2005;235:259–265
  3. White CS, Sali AI, Meyer CA. Missed lung cancer on chest radiography and computed tomography: imaging and medico-legal issues. J Thorac Imaging. 1999;14:63–68
  4. Muhm JR, Miller WE, Fontana RS, et al. Lung cancer detected during a screening program using four month chest radiographs. Radiology. 1983;148:609–615
  5. Quekel LG, Kessels AG, Goei R, van Engelshoven JM. Miss rate of lung cancer on the chest radiograph in clinical practice. Chest. 1999;115:720–724
  6. Shah PK, Austin JH, White CS, et al. Missed non-small cell lung cancer: radiographic findings of potentially respectable lesions evident only in retrospect. Radiology. 2003;226:235–241
  7. Gavelli G, Giampalma E. Sensitivity and specificity of chest X-ray screening for lung cancer. In: Proceedings of the international conference on prevention and early diagnosis of lung cancer. Varese, Italy. 1998;p. 103–108
  8. Burgess AE, Wagner RF, Jennings RJ. Human signal detection performance for noisy medical images. IEEE Computer Soc Int Workshop Med Imaging. 1982;88–105
  9. Samei E, Flynn MJ, Eyler WR. Detection of subtle lung nodules: relative influence of quantum and anatomic noise on chest radiographs. Radiology. 1999;213:727–734
  10. Kundel HL, Revesz G. Lesion conspicuity, structured noise, and film reader error. Am J Roentgenol. 1976;126:1233–1238
  11. Boynton RM, Bush WR. Recognition of forms against a complex background. J Opt Soc Am. 1956;46:758–764
  12. Revesz G, Kundel HL, Graber MA. The influence of structured noise on the detection of radiologic abnormalities. Invest Radiol. 1974;9:479–486
  13. Bick U, Diekmann F. Digital mammography: what do we and what don’t we know. Eur Radiol. 2007;17:1931–1942
  14. Astley SM. Computer-aided detection for screening mammography (review). Clin Radiol. 2004;59:390–399
  15. van Ginneken B, te Haar Roemny BM, Viergever MA. Computer-aided diagnosis in chest radiography: a survey. IEEE. 2001;20(12):1228–1241
  16. Matsumoto T, Doi K, Kano A, Nakamura H, Nakanishi T. Evaluation of the potential benefit of computer-aided (CAD) for lung cancer screenings using photofluorography: analysis of an observer study. Nippon Acta Radiol. 1993;53:1195–1207
  17. Warren Burhenne LJ, Wood SA, D-Orsi CJ, et al. Potential contribution of computer-aided detection to the sensitivity of screening mammography. Radiology. 2000;215:554–562
  18. Chen JJ, White CS. Use of CAD to evaluate lung cancer on chest radiography. J Thorac Imaging. 2008;23(2):93–96
  19. Kobayashi T, Xu XW, MacMahon H, Metz CE, Doi K. Effect of a computer-aided diagnosis scheme on radiologists performance in detection of lung nodules on radiographs. Radiology. 1996;199:843–848
  20. MacMahon H, Engelmann R, Behlen FM, et al. Computer-aided diagnosis of pulmonary nodules: results of a large scale observer test. Radiology. 1999;213:723–726
  21. Kakeda S, Moriya J, Sato H, et al. Improved detection of lung nodules on chest radiographs using a commercial computer-aided diagnosis system. AJR. 2004;182:505–510
  22. Shiraishi J, Katsuragawa S, Ikezoe J, et al. Development of a digital image database for chest radiographs with and without a lung nodule: receiver operating characteristic analysis of radiologists’ detection of pulmonary nodules. AJR. 2000;174:71–74
  23. Song W, Fan L, Xie Y, Qian JZ, Jin Z. A study of inter-observer variations of pulmonary nodule marking and characterizing on DR images. Proc SPIE. 2005;5749:272–280
  24. Bley TA, Baumann T, Saueressig U, et al. Comparison of radiologist and CAD performance in the detection of CT confirmed subtle pulmonary nodules on digital chest radiographs. Invest Radiol. 2008;43(Suppl. 16):
  25. Schilham A, van Ginneken B, Loog M. A computer-aided diagnosis system for detection of lung nodules in chest radiographs with an evaluation on a public database. Med Image Anal. 2006;10:247–258
  26. Hardie RC, Rogers SK, Wilson T, Rogers A. Performance analysis of a new computer aided detection system for identifying lung nodules on chest radiographs. Med Image Anal. 2008;12:240–258
  27. Kasai S, Li F, Shiraishi J, Dois K. Usefulness of computer-aided diagnosis schemes for vertebral fractures and lung nodules on chest radiographs. AJR. 2008;191:260–265
  28. van Beek EJR, Mullan B, Thompson B. Evaluation of a real-time interactive pulmonary nodule analysis system on chest digital radiographic studies: a prospective study. Acad Radiol. 2008;15:571–575
  29. Sakai S, Soeda H, Takahashi N, et al. Computer-aided nodule detection on digital chest radiography: validation test on consecutive T1 cases of respectable lung cancer. J Digit Imaging. 2006;19(4):376–382
  30. White CS, Flukinger T, Jeudy J. Use of a computer-aided detection system to detect missed lung cancer on chest radiography. Radiol Soc N Am. 2006;(abstract)
  31. Li F, Engelmann R, Metz CE, Doi K, MacMahon H. Lung cancers missed on chest radiographs: results obtained with a commercial computer-aided detection program. Radiology. 2008;246(1):273–280
  32. Gietema HA, Schaefer-Prokop CM, Mali W, Groenewegen G, Prokop M. Pulmonary nodules: interscan variability of semiautomatied volume measurements with multisection CT: influences of inspirations level, nodule size and segmentation performance. Radiology. 2007;245(3):888–894
  33. Shiraishi J, Abe H, Engelmann R, et al. Computer-aided diagnosis to distinguish benign from malignant solitary nodules on radiographs: ROC analysis of radiologists’ performance—initial experience. Radiology. 2003;227:469–474
  34. Shiraishi J, Hiroyuki A, Li F, et al. Computer-aided diagnosis for the detection and classification of lung cancers on chest radiographs: ROC analysis of radiologists’ performance; 2006.
  35. Gur D. Imaging technology and practice assessment studies: importance of the baseline or reference performance level. Radiology. 2008;247:8–11
  36. Freedman M, Osicka T. Reader variability: what we can learn from computer-aided detection experiments. JACR. 2006;3(6):446–455
  37. He Q, He W, Wang K, Ma D. Effect of multislice processing in digital chest radiography on automated detection of lung nodule with a computer assistance system. J Digit Imaging. 2008;21(Suppl. 1):S164
  38. MacMahon H. Advanced image processing and computer-aided diagnosis: are we there yet?. Editorial J Thorac Imaging. 2008;23(2):75–76

PII: S0720-048X(09)00352-0

doi: 10.1016/j.ejrad.2009.05.062

European Journal of Radiology
Volume 72, Issue 2 , Pages 218-225 , November 2009

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