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Volumn 7, Issue 2, 2012, Pages 323-329

Building an ensemble system for diagnosing masses in mammograms

Author keywords

CADx; Ensemble learning; Mass classification; Mass segmentation

Indexed keywords

ADULT; AGE; ARTICLE; BENIGN TUMOR; DATA BASE; DIAGNOSTIC ACCURACY; DIFFERENTIAL DIAGNOSIS; DIGITAL DATABASE FOR SCREENING MAMMOGRAPHY; HUMAN; IMAGE ENHANCEMENT; LEARNING; MAJOR CLINICAL STUDY; MALIGNANT NEOPLASTIC DISEASE; MAMMOGRAPHY; MEDICAL SPECIALIST; PRIORITY JOURNAL; REGION OF INTEREST; TUMOR CLASSIFICATION;

EID: 84862995297     PISSN: 18616410     EISSN: 18616429     Source Type: Journal    
DOI: 10.1007/s11548-011-0628-7     Document Type: Article
Times cited : (47)

References (27)
  • 3
    • 32044457119 scopus 로고    scopus 로고
    • Approaches for automated detection and classification of masses in mammo-grams
    • doi:10.1016/j.patcog.2005.07.006
    • Cheng HD, Shi XJ, Min R, Hu LM, Cai XP et al (2006) Approaches for automated detection and classification of masses in mammo-grams. Pattern Recognit. doi:10.1016/j.patcog.2005.07.006
    • (2006) Pattern Recognit
    • Cheng, H.D.1    Shi, X.J.2    Min, R.3    Hu, L.M.4    Cai, X.P.5
  • 4
    • 55349142869 scopus 로고    scopus 로고
    • Automated detection of breast mass spiculation levels and evaluation of scheme performance
    • doi:10.1016/j.acra.2008.07.015
    • Jiang L, Song E, Xu X, Ma G, Zhang B (2008) Automated detection of breast mass spiculation levels and evaluation of scheme performance. Acad Radiol. doi:10.1016/j.acra.2008.07.015
    • (2008) Acad Radiol
    • Jiang, L.1    Song, E.2    Xu, X.3    Ma, G.4    Zhang, B.5
  • 5
    • 0032129152 scopus 로고    scopus 로고
    • Automated seeded lesion seg-mentationondigital mammograms
    • doi:10. 1109/42.730396
    • Kupinski MA, Giger ML (1998) Automated seeded lesion seg- mentationondigital mammograms. IEEE Trans Med Imag. doi:10. 1109/42.730396
    • (1998) IEEE Trans Med Imag
    • Kupinski, M.A.1    Giger, M.L.2
  • 8
    • 35648984504 scopus 로고    scopus 로고
    • A dualstage method for lesion segmentation on digital mammograms
    • doi:10.1118/1.2790837
    • Yuan Y, Giger ML, Li H, Suzuki K, Sennett C (2007) A dualstage method for lesion segmentation on digital mammograms. Med Phys 34:4180-4193. doi:10.1118/1.2790837
    • (2007) Med Phys , vol.34 , pp. 4180-4193
    • Yuan, Y.1    Giger, M.L.2    Li, H.3    Suzuki, K.4    Sennett, C.5
  • 12
    • 59149100526 scopus 로고    scopus 로고
    • Toward breast cancer diagnosis based on automated segmentation of masses in mammograms
    • doi:10.1016/j.patcog.2008.08.006
    • Domínguez1 AR, Nandi AK (2009) Toward breast cancer diagnosis based on automated segmentation of masses in mammograms. Pattern Recognit. doi:10.1016/j.patcog.2008.08.006
    • (2009) Pattern Recognit
    • Domínguez, A.R.1    Nandi, A.K.2
  • 13
    • 34547591212 scopus 로고    scopus 로고
    • Characterization of mammographic masses using a gradient-based segmentation algorithm and a neural classifier
    • doi:10. 1016/j.compbiomed.2007.01.009
    • Delogu P, Fantacci M, Kasae P, Retico A (2007) Characterization of mammographic masses using a gradient-based segmentation algorithm and a neural classifier. Comput Biol Med. doi:10. 1016/j.compbiomed.2007.01.009
    • (2007) Comput Biol Med
    • Delogu, P.1    Fantacci, M.2    Kasae, P.3    Retico, A.4
  • 15
    • 65449116355 scopus 로고    scopus 로고
    • A modular framework for multicategory feature selection in digital mammography
    • ISBN 2-930307-04-8
    • Ghosh R, Ghosh M, Yearwood J (2004) A modular framework for multicategory feature selection in digital mammography. ESANN'2004 proceedings, pp 175-180. ISBN 2-930307-04-8
    • (2004) ESANN'2004 Proceedings , pp. 175-180
    • Ghosh, R.1    Ghosh, M.2    Yearwood, J.3
  • 16
    • 17444397485 scopus 로고    scopus 로고
    • Neural vs. statistical classifier in conjunction with genetic algorithm based feature selection
    • doi:10.1016/j.patrec.2004.09.053
    • Zhang P, Verma B, Kumar K (2005) Neural vs. statistical classifier in conjunction with genetic algorithm based feature selection. Pattern Recognit Lett. doi:10.1016/j.patrec.2004.09.053
    • (2005) Pattern Recognit Lett
    • Zhang, P.1    Verma, B.2    Kumar, K.3
  • 17
    • 0000551189 scopus 로고    scopus 로고
    • Popular ensemble methods: An empirical study
    • doi:10.1613/jair.614
    • Opitz D, Maclin R (1999) Popular ensemble methods: an empirical study. J Artif Intell Res. doi:10.1613/jair.614
    • (1999) J Artif Intell Res
    • Opitz, D.1    MacLin, R.2
  • 18
    • 12144288329 scopus 로고    scopus 로고
    • Is combining classifiers with stacking better than selecting the best one?
    • doi:10.1023/B:MACH.0000015881.36452.6e
    • Dzeroski S, Zenko B (2004) Is combining classifiers with stacking better than selecting the best one? Mach Learn. doi:10.1023/B:MACH.0000015881.36452.6e
    • (2004) Mach Learn
    • Dzeroski, S.1    Zenko, B.2
  • 19
    • 0030211964 scopus 로고    scopus 로고
    • Bagging predictors
    • Breiman L (1996) Bagging predictors. Mach Learn 24:123-140
    • (1996) Mach Learn , vol.24 , pp. 123-140
    • Breiman, L.1
  • 20
    • 0026692226 scopus 로고
    • Stacked generalization
    • Wolper DH (1992) Stacked generalization. Neural Netw 5:241-259
    • (1992) Neural Netw , vol.5 , pp. 241-259
    • Wolper, D.H.1
  • 21
    • 0033343146 scopus 로고    scopus 로고
    • Issues in stacked generalization
    • Ting K, Witten I (1999) Issues in stacked generalization. J Artif Intell Res 10:271-289
    • (1999) J Artif Intell Res , vol.10 , pp. 271-289
    • Ting, K.1    Witten, I.2
  • 25
    • 58149184001 scopus 로고    scopus 로고
    • Shape and texture feature extraction for retrieval mammogram in databases
    • Choras R (2008) Shape and texture feature extraction for retrieval mammogram in databases. Inf Tech Biomed 47:121-128
    • (2008) Inf Tech Biomed , vol.47 , pp. 121-128
    • Choras, R.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.