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Volumn 36, Issue 9, 2005, Pages 65-76

Enhancement of CAD system for breast cancers by improvement of classifiers

Author keywords

CAD; Classifier; Generalized Mahalanobis distance; Mammography; MLP

Indexed keywords

COMPUTER AIDED DIAGNOSIS; DIAGNOSIS; IMAGE ANALYSIS; MAMMOGRAPHY; RADIOGRAPHY; X RAYS;

EID: 22544452427     PISSN: 08821666     EISSN: None     Source Type: Journal    
DOI: 10.1002/scj.20173     Document Type: Article
Times cited : (2)

References (14)
  • 2
    • 22544485851 scopus 로고    scopus 로고
    • Performance studies of a computer-aided diagnostic system on mammograms
    • Karssmeijer N et al.
    • Hara T, Fujita H et al. Performance studies of a computer-aided diagnostic system on mammograms. In: Karssmeijer N et al. Digital mammography, p 407-410, 1998.
    • (1998) Digital Mammography , pp. 407-410
    • Hara, T.1    Fujita, H.2
  • 3
    • 0008438303 scopus 로고    scopus 로고
    • Prospective testing of a clinical mammography workstation for CAD: Analysis of first 10,000 cases
    • Karssemeijer N et al.
    • Nishikawa RM, Giger ML et al. Prospective testing of a clinical mammography workstation for CAD: Analysis of first 10,000 cases. In: Karssemeijer N et al. Digital mammography, p 401-406, 1998.
    • (1998) Digital Mammography , pp. 401-406
    • Nishikawa, R.M.1    Giger, M.L.2
  • 5
    • 0027512684 scopus 로고
    • Artificial neural networks in mammography: Application to decision making in the diagnosis of breast cancer
    • Wu Y, Giger ML, Doi K, Vybomy CJ, Schmidt RA, Mets CE. Artificial neural networks in mammography: Application to decision making in the diagnosis of breast cancer. Radiology 1993;187:81-87.
    • (1993) Radiology , vol.187 , pp. 81-87
    • Wu, Y.1    Giger, M.L.2    Doi, K.3    Vybomy, C.J.4    Schmidt, R.A.5    Mets, C.E.6
  • 7
    • 0025490985 scopus 로고
    • Networks for approximation and learning
    • Possio T, Girosi F. Networks for approximation and learning. Proc IEEE 1990;78:1481-1497.
    • (1990) Proc IEEE , vol.78 , pp. 1481-1497
    • Possio, T.1    Girosi, F.2
  • 8
    • 0022471098 scopus 로고
    • Learning representations by back-propagating errors
    • Rumelhart DE, Hinton GE, Williams RJ. Learning representations by back-propagating errors. Nature 1986;323:533-536.
    • (1986) Nature , vol.323 , pp. 533-536
    • Rumelhart, D.E.1    Hinton, G.E.2    Williams, R.J.3
  • 10
  • 12
    • 3042553281 scopus 로고    scopus 로고
    • Tests of statistically significant differences between two imaging systems in ROC analysis. Use of the jackknife method and its applications
    • Shiraishi J, Utsunomiya A. Tests of statistically significant differences between two imaging systems in ROC analysis. Use of the jackknife method and its applications. Radio Technol 1997;53:691-698.
    • (1997) Radio Technol , vol.53 , pp. 691-698
    • Shiraishi, J.1    Utsunomiya, A.2
  • 13
    • 11444255899 scopus 로고    scopus 로고
    • Current status and future of the CAD overview of computer-aided diagnosis
    • Ishida T, Katsuragawa S. Current status and future of the CAD overview of computer-aided diagnosis. Nippon Acta Radiol 2002;62:404-408.
    • (2002) Nippon Acta Radiol , vol.62 , pp. 404-408
    • Ishida, T.1    Katsuragawa, S.2
  • 14
    • 22544454032 scopus 로고    scopus 로고
    • Judgement of the diagnostic efficiency and ROC analysis in terms of the digital image diagnosis
    • Shiraishi J. Judgement of the diagnostic efficiency and ROC analysis in terms of the digital image diagnosis. Jpn J Radiol Technol 2002;58:15-19.
    • (2002) Jpn J Radiol Technol , vol.58 , pp. 15-19
    • Shiraishi, J.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.