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Volumn 15, Issue 1, 2016, Pages

Computer-aided detection (CADe) and diagnosis (CADx) system for lung cancer with likelihood of malignancy

Author keywords

CADe and CADx; Computer aided detection system; Detection of pulmonary nodules; Likelihood of malignancy; Lung cancer diagnosis; Medical image analysis

Indexed keywords

BIOLOGICAL ORGANS; COMPUTER AIDED ANALYSIS; COMPUTERIZED TOMOGRAPHY; DECISION MAKING; DIAGNOSIS; DISEASES; FEATURE EXTRACTION; MEDICAL IMAGING; SUPPORT VECTOR MACHINES;

EID: 84954402867     PISSN: None     EISSN: 1475925X     Source Type: Journal    
DOI: 10.1186/s12938-015-0120-7     Document Type: Article
Times cited : (203)

References (48)
  • 2
    • 79958043675 scopus 로고    scopus 로고
    • SEER Cancer Statistics Review, 1975-2011
    • Accessed: 21 Jul.
    • U.S.N.I. of Health. SEER Cancer Statistics Review, 1975-2011. http://seer.cancer.gov/archive/csr/1975_2011/. Accessed: 21 Jul 2015.
    • (2015)
  • 3
    • 34247245110 scopus 로고    scopus 로고
    • Recent progress in computer-aided diagnosis of lung nodules on thin-section CT
    • Li Q. Recent progress in computer-aided diagnosis of lung nodules on thin-section CT. Comput Med Imaging Graph. 2007;31(4-5):248-57.
    • (2007) Comput Med Imaging Graph , vol.31 , Issue.4-5 , pp. 248-257
    • Li, Q.1
  • 4
    • 1642580603 scopus 로고    scopus 로고
    • Pulmonary nodules at chest ct: effect of computer-aided diagnosis on radiologists' detection performance
    • Kazuo A, Kohei M, Akio O, Masanori K, Haruo H, Shinichi H, Yasumasa N. Pulmonary nodules at chest ct: effect of computer-aided diagnosis on radiologists' detection performance. Radiology. 2004;230:347-52.
    • (2004) Radiology , vol.230 , pp. 347-352
    • Kazuo, A.1    Kohei, M.2    Akio, O.3    Masanori, K.4    Haruo, H.5    Shinichi, H.6    Yasumasa, N.7
  • 5
    • 84878829657 scopus 로고    scopus 로고
    • A review of computer-aided diagnosis in thoracic and colonic imaging
    • Suzuki K. A review of computer-aided diagnosis in thoracic and colonic imaging. Quantitative Imag Med Surg. 2012;2(3):163-76.
    • (2012) Quantitative Imag Med Surg , vol.2 , Issue.3 , pp. 163-176
    • Suzuki, K.1
  • 7
    • 0038710369 scopus 로고    scopus 로고
    • Massive training artificial neural network (mtann) for reduction of false positives in computerized detection of lung nodules in low-dose computed tomography
    • Suzuki K, Armato III 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. Medical Physics. 2003;30(7):1602-17.
    • (2003) Medical Physics , vol.30 , Issue.7 , pp. 1602-1617
    • Suzuki, K.1    Armato, S.G.2    Li, F.3    Sone, S.4    Doi, K.5
  • 8
    • 77951647196 scopus 로고    scopus 로고
    • A new computationally efficient CAD system for pulmonary nodule detection in CT imagery
    • Messay T, Hardie RC, Rogers SK. A new computationally efficient CAD system for pulmonary nodule detection in CT imagery. Med Image Anal. 2010;14(3):390-406.
    • (2010) Med Image Anal , vol.14 , Issue.3 , pp. 390-406
    • Messay, T.1    Hardie, R.C.2    Rogers, S.K.3
  • 9
    • 80053608049 scopus 로고    scopus 로고
    • A novel computer-aided lung nodule detection system for ct images
    • Tan M, Deklerck R, Jansen B, Bister M, Cornelis J. A novel computer-aided lung nodule detection system for ct images. Med Phys. 2011;38(10):5630-45.
    • (2011) Med Phys , vol.38 , Issue.10 , pp. 5630-5645
    • Tan, M.1    Deklerck, R.2    Jansen, B.3    Bister, M.4    Cornelis, J.5
  • 10
    • 84867731465 scopus 로고    scopus 로고
    • Automatic detection of lung nodules in ct datasets based on stable 3d mass-spring models
    • Cascio D, Magro R, Fauci F, Iacomi M, Raso G. Automatic detection of lung nodules in ct datasets based on stable 3d mass-spring models. Comput Biol Med. 2012;42(11):1098-109.
    • (2012) Comput Biol Med , vol.42 , Issue.11 , pp. 1098-1109
    • Cascio, D.1    Magro, R.2    Fauci, F.3    Iacomi, M.4    Raso, G.5
  • 11
    • 84878889029 scopus 로고    scopus 로고
    • Fast lung nodule detection in chest ct images using cylindrical nodule-enhancement filter
    • Teramoto A, Fujita H. Fast lung nodule detection in chest ct images using cylindrical nodule-enhancement filter. Int J Comp Assist Radiol Surg. 2013;8(2):193-205.
    • (2013) Int J Comp Assist Radiol Surg , vol.8 , Issue.2 , pp. 193-205
    • Teramoto, A.1    Fujita, H.2
  • 12
    • 84924738641 scopus 로고    scopus 로고
    • Fast and adaptive detection of pulmonary nodules in thoracic ct images using a hierarchical vector quantization scheme
    • Han H, Li L, Han F, Song B, Moore W, Liang Z. Fast and adaptive detection of pulmonary nodules in thoracic ct images using a hierarchical vector quantization scheme. IEEE J Biomed Health Inform. 2015;19(2):648-59.
    • (2015) IEEE J Biomed Health Inform , vol.19 , Issue.2 , pp. 648-659
    • Han, H.1    Li, L.2    Han, F.3    Song, B.4    Moore, W.5    Liang, Z.6
  • 13
    • 84924051480 scopus 로고    scopus 로고
    • Shape and texture based novel features for automated juxtapleural nodule detection in lung cts
    • Taşci E, Uğur A. Shape and texture based novel features for automated juxtapleural nodule detection in lung cts. J Med Syst 2015;39(5).
    • (2015) J Med Syst , vol.39 , Issue.5
    • Taşci, E.1    Uğur, A.2
  • 16
    • 67649607477 scopus 로고    scopus 로고
    • Computer-aided diagnosis of pulmonary nodules on ct scans: Improvement of classification performance with nodule surface features
    • Way TW, Sahiner B, Chan H-P, Hadjiiski L, Cascade PN, Chughtai A, Bogot N, Kazerooni E. Computer-aided diagnosis of pulmonary nodules on ct scans: Improvement of classification performance with nodule surface features. Med Phys. 2009;36(7):3086-98.
    • (2009) Med Phys , vol.36 , Issue.7 , pp. 3086-3098
    • Way, T.W.1    Sahiner, B.2    Chan, H.-P.3    Hadjiiski, L.4    Cascade, P.N.5    Chughtai, A.6    Bogot, N.7    Kazerooni, E.8
  • 17
    • 25144514408 scopus 로고    scopus 로고
    • Computer-aided diagnostic scheme for distinction between benign and malignant nodules in thoracic low-dose ct by use of massive training artificial neural network
    • Suzuki K, Li F, Sone S, Doi K. Computer-aided diagnostic scheme for distinction between benign and malignant nodules in thoracic low-dose ct by use of massive training artificial neural network. IEEE Trans Med Imag. 2005;24(9):1138-50.
    • (2005) IEEE Trans Med Imag , vol.24 , Issue.9 , pp. 1138-1150
    • Suzuki, K.1    Li, F.2    Sone, S.3    Doi, K.4
  • 18
    • 77955268440 scopus 로고    scopus 로고
    • Computer-aided diagnosis of pulmonary nodules using a two-step approach for feature selection and classifier ensemble construction
    • (Knowledge Discovery and Computer-Based Decision Support in Biomedicine)
    • Lee MC, Boroczky L, Sungur-Stasik K, Cann AD, Borczuk AC, Kawut SM, Powell CA. Computer-aided diagnosis of pulmonary nodules using a two-step approach for feature selection and classifier ensemble construction. Artif Intel Med. 2010; 50(1):43-53 (Knowledge Discovery and Computer-Based Decision Support in Biomedicine)
    • (2010) Artif Intel Med , vol.50 , Issue.1 , pp. 43-53
    • Lee, M.C.1    Boroczky, L.2    Sungur-Stasik, K.3    Cann, A.D.4    Borczuk, A.C.5    Kawut, S.M.6    Powell, C.A.7
  • 19
    • 84946235133 scopus 로고    scopus 로고
    • Automated system for lung nodules classification based on wavelet feature descriptor and support vector machine
    • Orozco H, Villegas O, Sánchez V, Domínguez H, Alfaro M. Automated system for lung nodules classification based on wavelet feature descriptor and support vector machine. BioMed Eng. 2015;14(9).
    • (2015) BioMed Eng , vol.14 , Issue.9
    • Orozco, H.1    Villegas, O.2    Sánchez, V.3    Domínguez, H.4    Alfaro, M.5
  • 20
    • 77953261305 scopus 로고    scopus 로고
    • Cad (computed-aided detection) and cadx (computer aided diagnosis) systems in identifying and characterising lung nodules on chest ct: overview of research, developments and new prospects
    • Fraioli F, Serra G, Passariello R. Cad (computed-aided detection) and cadx (computer aided diagnosis) systems in identifying and characterising lung nodules on chest ct: overview of research, developments and new prospects. La radiologia medica. 2010;115(3):385-402.
    • (2010) La radiologia medica , vol.115 , Issue.3 , pp. 385-402
    • Fraioli, F.1    Serra, G.2    Passariello, R.3
  • 22
    • 84899652536 scopus 로고    scopus 로고
    • Computer-aided detection system for lung cancer in computed tomography scans: review and future prospects
    • Firmino M, Morais AH, Mendoca RM, Dantas MR, Hekis HR, Valentim R. Computer-aided detection system for lung cancer in computed tomography scans: review and future prospects. BioMed Eng. 2014; 13(41).
    • (2014) BioMed Eng , vol.13 , Issue.41
    • Firmino, M.1    Morais, A.H.2    Mendoca, R.M.3    Dantas, M.R.4    Hekis, H.R.5    Valentim, R.6
  • 23
    • 79551672468 scopus 로고    scopus 로고
    • The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI): a completed reference database of lung nodules on CT scans
    • Sg A, et al. The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI): a completed reference database of lung nodules on CT scans. Med Phys. 2011;38(2):915-31.
    • (2011) Med Phys , vol.38 , Issue.2 , pp. 915-931
    • Sg, A.1
  • 24
    • 84954362223 scopus 로고    scopus 로고
    • Chapter 03-acquisition of medical image data
    • In: Bartz BP (ed.) The Morgan Kaufmann Series in Computer Graphics, Morgan Kaufmann, Burlington.
    • Preim B, Bartz D. Chapter 03-acquisition of medical image data. In: Bartz BP (ed.) Visualization in Medicine. The Morgan Kaufmann Series in Computer Graphics, Morgan Kaufmann, Burlington. 2007. p. 35-64.
    • (2007) Visualization in Medicine , pp. 35-64
    • Preim, B.1    Bartz, D.2
  • 25
    • 0003661003 scopus 로고    scopus 로고
    • Level set methods and fast marching methods: evolving interfaces in computational geometry, fluid mechanics, computer vision, and materials science, Cambridge monographs on applied and computational mathematics
    • Cambridge: Cambridge University Press;
    • Sethian JA. Level set methods and fast marching methods: evolving interfaces in computational geometry, fluid mechanics, computer vision, and materials science, Cambridge monographs on applied and computational mathematics. Cambridge: Cambridge University Press; 1999.
    • (1999)
    • Sethian, J.A.1
  • 27
    • 77951166786 scopus 로고    scopus 로고
    • Digital image processing for medical applications
    • 1st ed. USA: Cambridge University Press;
    • Dougherty G. Digital image processing for medical applications. 1st ed. USA: Cambridge University Press; 2009.
    • (2009)
    • Dougherty, G.1
  • 28
    • 84870908566 scopus 로고    scopus 로고
    • Label object representation and manipulation with ITK
    • Lehmann G. Label object representation and manipulation with ITK. Insight J 2007; 08
    • (2007) Insight J , pp. 08
    • Lehmann, G.1
  • 29
    • 0026172104 scopus 로고
    • Watersheds in digital spaces: an efficient algorithm based on immersion simulations
    • Vincent L, Soille P. Watersheds in digital spaces: an efficient algorithm based on immersion simulations. IEEE Trans Pat Anal Mach Intel. 1991;13(6):583-98.
    • (1991) IEEE Trans Pat Anal Mach Intel , vol.13 , Issue.6 , pp. 583-598
    • Vincent, L.1    Soille, P.2
  • 30
    • 84907263499 scopus 로고    scopus 로고
    • The watershed transform in itk-discussion and new developments
    • Beare R, Lehmann G. The watershed transform in itk-discussion and new developments. 2006.
    • (2006)
    • Beare, R.1    Lehmann, G.2
  • 32
    • 77953357021 scopus 로고    scopus 로고
    • Stepwise evolution from a focal pure pulmonary ground-glass opacity nodule into an invasive lung adenocarcinoma: An observation for more than 10 years
    • Min JH, Lee HY, Lee KS, Han J, Park K, Ahn M-J, Lee S-J. Stepwise evolution from a focal pure pulmonary ground-glass opacity nodule into an invasive lung adenocarcinoma: An observation for more than 10 years. Lung Cancer. 2010;69(1):123-6.
    • (2010) Lung Cancer , vol.69 , Issue.1 , pp. 123-126
    • Min, J.H.1    Lee, H.Y.2    Lee, K.S.3    Han, J.4    Park, K.5    Ahn, M.-J.6    Lee, S.-J.7
  • 33
    • 70449454316 scopus 로고    scopus 로고
    • The GLCM Tutorial Home Page
    • Current Version: 2.10.
    • Hall-Beyer M. The GLCM Tutorial Home Page. Current Version: 2.10. http://www.fp.ucalgary.ca/mhallbey/tutorial.htm
    • Hall-Beyer, M.1
  • 36
    • 58149421595 scopus 로고
    • Analysis of a complex of statistical variables into principal components
    • Hotelling H. Analysis of a complex of statistical variables into principal components. J Educ Psych. 1933;24:1-48.
    • (1933) J Educ Psych , vol.24 , pp. 1-48
    • Hotelling, H.1
  • 37
    • 80052440876 scopus 로고    scopus 로고
    • Directional features for automatic tumor classification of mammogram images
    • Buciu I, Gacsadi A. Directional features for automatic tumor classification of mammogram images. Biomed Signal Process Control. 2011;6(4):370-8.
    • (2011) Biomed Signal Process Control , vol.6 , Issue.4 , pp. 370-378
    • Buciu, I.1    Gacsadi, A.2
  • 38
    • 84899022480 scopus 로고    scopus 로고
    • Automatic choice of dimensionality for PCA
    • Minka TP. Automatic choice of dimensionality for PCA. Adv Neural Inform Process Syst. 2001;15:598-604.
    • (2001) Adv Neural Inform Process Syst , vol.15 , pp. 598-604
    • Minka, T.P.1
  • 40
    • 0003413187 scopus 로고    scopus 로고
    • Neural networks: a comprehensive foundation
    • 2nd ed. Upper Saddle River: Prentice Hall PTR;
    • Haykin S. Neural networks: a comprehensive foundation. 2nd ed. Upper Saddle River: Prentice Hall PTR; 1998.
    • (1998)
    • Haykin, S.1
  • 41
    • 34249753618 scopus 로고
    • Support-vector networks
    • Cortes C, Vapnik V. Support-vector networks. Mach Learn. 1995;20(3):273-97.
    • (1995) Mach Learn , vol.20 , Issue.3 , pp. 273-297
    • Cortes, C.1    Vapnik, V.2
  • 42
    • 36148956597 scopus 로고    scopus 로고
    • The lung image database consortium (lidc) data collection process for nodule detection and annotation
    • McNitt-Gray MF, et al. The lung image database consortium (lidc) data collection process for nodule detection and annotation. Acad Radiol. 2007;14(12):1464-74.
    • (2007) Acad Radiol , vol.14 , Issue.12 , pp. 1464-1474
    • McNitt-Gray, M.F.1
  • 43
    • 0003873913 scopus 로고    scopus 로고
    • The Visualization Toolkit
    • 4th ed. Clifton Park: Kitware Inc;
    • Schroeder W, Martin KM, Lorensen WE. The Visualization Toolkit. 4th ed. Clifton Park: Kitware Inc; 2006.
    • (2006)
    • Schroeder, W.1    Martin, K.M.2    Lorensen, W.E.3
  • 44
    • 0003250435 scopus 로고
    • Single-layer learning revisited: a stepwise procedure for building and training a neural network
    • In: Soulie F, Hérault J, editors. NATO ASI SeriesBerlin Heidelberg: Springer;
    • Knerr S, Personnaz L, Dreyfus G. Single-layer learning revisited: a stepwise procedure for building and training a neural network. In: Soulie F, Hérault J, editors. Neurocomputing, vol. 68., NATO ASI SeriesBerlin Heidelberg: Springer; 1990. p. 41-50.
    • (1990) Neurocomputing , vol.68 , pp. 41-50
    • Knerr, S.1    Personnaz, L.2    Dreyfus, G.3
  • 45
    • 0003684449 scopus 로고    scopus 로고
    • The elements of statistical learning data mining, inference, and prediction
    • 2nd ed. Stanford: Springer;
    • Hastie T, Tibshirani R, Friedman J. The elements of statistical learning data mining, inference, and prediction. 2nd ed. Stanford: Springer; 2008.
    • (2008)
    • Hastie, T.1    Tibshirani, R.2    Friedman, J.3
  • 46
    • 10044283198 scopus 로고    scopus 로고
    • The Optimality of Naive Bayes
    • In: Barr V, Markov Z, editors. Miami Beach, Florida: AAAI Press;
    • Zhang H. The Optimality of Naive Bayes. In: Barr V, Markov Z, editors. FLAIRS Conference. Miami Beach, Florida: AAAI Press; 2004.
    • (2004) FLAIRS Conference
    • Zhang, H.1
  • 47
    • 0036851688 scopus 로고    scopus 로고
    • Lung nodule detection on thoracic computed tomography images: preliminary evaluation of a computer-aided diagnosis system
    • Gurcan MN, Sahiner B, Petrick N, Chan HP, Kazerooni EA, Cascade PN, Hadjiiski L. Lung nodule detection on thoracic computed tomography images: preliminary evaluation of a computer-aided diagnosis system. Med Phys. 2002;28:2552-8.
    • (2002) Med Phys , vol.28 , pp. 2552-2558
    • Gurcan, M.N.1    Sahiner, B.2    Petrick, N.3    Chan, H.P.4    Kazerooni, E.A.5    Cascade, P.N.6    Hadjiiski, L.7
  • 48
    • 33645886615 scopus 로고    scopus 로고
    • Pulmonary nodule detection in CT images with quantized convergence index filter
    • (Special Issue on The Second International Workshop on Biomedical Image Registration (WBIR'03))
    • Matsumoto S, Kundel HL, Gee JC, Gefter WB, Hatabu H. Pulmonary nodule detection in CT images with quantized convergence index filter. Med Image Anal. 2006;10(3):343-352. (Special Issue on The Second International Workshop on Biomedical Image Registration (WBIR'03))
    • (2006) Med Image Anal , vol.10 , Issue.3 , pp. 343-352
    • Matsumoto, S.1    Kundel, H.L.2    Gee, J.C.3    Gefter, W.B.4    Hatabu, H.5


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