Machine learning in computer-aided diagnosis of the thorax and colon in CT: A survey

IEICE Transactions on Information and Systems

Volumn E96-D, Issue 4, 2013, Pages 772-783

  Suzuki, Kenji ^a  

^a UNIVERSITY OF CHICAGO   (United States)

Author keywords

Classification; Colorectal polyp; Computer aided diagnosis; CT colonography; Lung nodule; Machine learning in medical imaging; Pixel based machine learning

Indexed keywords

BIOLOGICAL ORGANS; CLASSIFICATION (OF INFORMATION); COMPUTERIZED TOMOGRAPHY; DISCRIMINANT ANALYSIS; IMAGE SEGMENTATION; MAMMOGRAPHY; MEDICAL IMAGING; PATTERN RECOGNITION; SUPPORT VECTOR MACHINES; SURVEYS;

COLORECTAL POLYPS; COMPUTER-AIDED DETECTION; CT COLONOGRAPHY; DETECTION AND DIAGNOSIS; LINEAR DISCRIMINANT ANALYSIS; LUNG NODULE; MEDICAL PATTERN RECOGNITION; QUADRATIC DISCRIMINANT ANALYSIS;

COMPUTER AIDED DIAGNOSIS;

EID: 84878237804     PISSN: 09168532     EISSN: 17451361     Source Type: Journal    
DOI: 10.1587/transinf.E96.D.772     Document Type: Review

References (134)

1. M.L. Giger and K. Suzuki, "Computer-aided diagnosis (CAD)," in Biomedical Information Technology, ed. D.D. Feng, pp.359-374, Academic Press, 2007.
2. K. Doi, "Current status and future potential of computer-aided diagnosis in medical imaging," Br J Radiol, vol.78, Spec no.1, pp.S3-S19, 2005.
3. H.P. Chan, B. Sahiner, M.A. Helvie, N. Petrick, M.A. Roubidoux, T.E. Wilson, D.D. Adler, C. Paramagul, J.S. Newman, and S. Sanjay-Gopal, "Improvement of radiologists' characterization of mammographic masses by using computer-aided diagnosis: an ROC study," Radiology, vol.212, no.3, pp.817-827, Sept. 1999.
4. F. Li, M. Aoyama, J. Shiraishi, H. Abe, Q. Li, K. Suzuki, R. Engelmann, S. Sone, H. Macmahon, and K. Doi, "Radiologists' performance for differentiating benign from malignant lung nodules on high-resolution CT using computer-estimated likelihood of malignancy," AJR. Am. J. Roentgenol., vol.183, no.5, pp.1209-1215, Nov. 2004.
5. F. Li, H. Arimura, K. Suzuki, J. Shiraishi, Q. Li, H. Abe, R. Engelmann, S. Sone, H. MacMahon, and K. Doi, "Computeraided detection of peripheral lung cancers missed at CT: ROC analyses without and with localization," Radiology, vol.237, no.2, pp.684-690, Nov. 2005.
6. K. Suzuki, M. Hori, E. McFarland, A.C. Friedman, D.C. Rockey, and A.H. Dachman, "Can CAD help improve the performance of radiologists in detection of difficult polyps in CT colonography?," Proc. RSNA Annual Meeting, pp.872, Chicago, IL, 2009.
7. K. Suzuki, J. Shiraishi, H. Abe, H. MacMahon, and K. Doi, "Falsepositive reduction in computer-aided diagnostic scheme for detecting nodules in chest radiographs by means of massive training artificial neural network," Academic Radiology, vol.12, no.2, pp.191-201, Feb. 2005.
8. B. van Ginneken, B.M. ter Haar Romeny, and M.A. Viergever, "Computer-aided diagnosis in chest radiography: A survey," IEEE Trans. Med. Imaging, vol.20, no.12, pp.1228-1241, Dec. 2001.
9. M.L. Giger, K. Doi, and H. MacMahon, "Image feature analysis and computer-aided diagnosis in digital radiography. 3. Automated detection of nodules in peripheral lung fields," Med. Phys., vol.15, no.2, pp.158-166, March-April 1988.
10. S. Chen, K. Suzuki, and H. MacMahon, "A computer-aided diagnostic scheme for lung nodule detection in chest radiographs by means of two-stage nodule-enhancement with support vector classification," Med. Phys., vol.38, pp.1844-1858, 2011.
11. K. Suzuki, S.G. Armato, F. Li, S. Sone, and K. Doi, "Massive training artificial neural network (MTANN) for reduction of false positives in computerized detection of lung nodules in low-dose CT," Med. Phys., vol.30, no.7, pp.1602-1617, July 2003.
12. H. Arimura, S. Katsuragawa, K. Suzuki, F. Li, J. Shiraishi, S. Sone, and K. Doi, "Computerized scheme for automated detection of lung nodules in low-dose computed tomography images for lung cancer screening," Acad. Radiol., vol.11, no.6, pp.617-629, June 2004.
13. S.G. Armato, 3rd, M.L. Giger, C.J. Moran, J.T. Blackburn, K. Doi, and H. MacMahon, "Computerized detection of pulmonary nodules on CT scans," Radiographics, vol.19, no.5, pp.1303-1311, Sept.-Oct. 1999.
14. S.G. Armato, 3rd, F. Li, M.L. Giger, H. MacMahon, S. Sone, and K. Doi, "Lung cancer: performance of automated lung nodule detection applied to cancers missed in a CT screening program," Radiology, vol.225, no.3, pp.685-692, Dec. 2002.
15. H.P. Chan, K. Doi, S. Galhotra, C.J. Vyborny, H. MacMahon, and P.M. Jokich, "Image feature analysis and computer-aided diagnosis in digital radiography. I. Automated detection of microcalcifications in mammography," Med. Phys., vol.14, no.4, pp.538-548, July-Aug. 1987.
16. K.G. Gilhuijs, M.L. Giger, and U. Bick, "Computerized analysis of breast lesions in three dimensions using dynamic magneticresonance imaging," Med. Phys., vol.25, no.9, pp.1647-1654, Sept. 1998.
17. K. Drukker, M.L. Giger, and C.E. Metz, "Robustness of computerized lesion detection and classification scheme across different breast US platforms," Radiology, vol.237, no.3, pp.834-840, Dec. 2005.
18. H. Yoshida and J. Nappi, "Three-dimensional computer-aided diagnosis scheme for detection of colonic polyps," IEEE Trans. Med. Imaging, vol.20, no.12, pp.1261-1274, Dec. 2001.
19. K. Suzuki, H. Yoshida, J. Nappi, and A.H. Dachman, "Massivetraining artificial neural network (MTANN) for reduction of false positives in computer-aided detection of polyps: Suppression of rectal tubes,"Medical Physics, vol.33, no.10, pp.3814-3824, 2006.
20. K. Suzuki, H. Yoshida, J. Nappi, S.G. Armato, 3rd, and A.H. Dachman, "Mixture of expert 3D massive-training ANNs for reduction of multiple types of false positives in CAD for detection of polyps in CT colonography," Med. Phys., vol.35, no.2, pp.694-703, Feb. 2008.
21. R.M. Summers, C.F. Beaulieu, L.M. Pusanik, J.D. Malley, R.B. Jeffrey, Jr., D.I. Glazer, and S. Napel, "Automated polyp detector for CT colonography: Feasibility study," Radiology, vol.216, no.1, pp.284-290, July 2000.
22. A. Lostumbo, C. Wanamaker, J. Tsai, K. Suzuki, and A.H. Dachman, "Comparison of 2D and 3D views for evaluation of flat lesions in CT colonography," Acad. Radiol., vol.17, no.1, pp.39-47, Jan. 2010.
23. A. Lostumbo, K. Suzuki, and A.H. Dachman, "Flat lesions in CT colonography," Abdom. Imaging, vol.35, no.5, pp.578-583, Oct. 2010.
24. D.E. Rumelhart, G.E. Hinton, and R.J. Williams, "Learning representations by back-propagating errors," Nature, vol.323, pp.533-536, 1986.
25. V.N. Vapnik, The Nature of Statistical Learning Theory, Springer-Verlag, Berlin, 1995.
26. J. Shiraishi, Q. Li, K. Suzuki, R. Engelmann, and K. Doi, "Computer-aided diagnostic scheme for the detection of lung nodules on chest radiographs: localized search method based on anatomical classification," Med. Phys., vol.33, no.7, pp.2642-2653, July 2006.
27. S.G. Armato, 3rd, M.L. Giger, and H. MacMahon, "Automated detection of lung nodules in CT scans: Preliminary results," Med. Phys., vol.28, no.8, pp.1552-1561, Aug. 2001.
28. M. Aoyama, Q. Li, S. Katsuragawa, H. MacMahon, and K. Doi, "Automated computerized scheme for distinction between benign and malignant solitary pulmonary nodules on chest images," Med. Phys., vol.29, no.5, pp.701-708, May 2002.
29. M. Aoyama, Q. Li, S. Katsuragawa, F. Li, S. Sone, and K. Doi, "Computerized scheme for determination of the likelihood measure of malignancy for pulmonary nodules on low-dose CT images," Med. Phys., vol.30, no.3, pp.387-394, March 2003.
30. A.K. Jerebko, R.M. Summers, J.D. Malley, M. Franaszek, and C.D. Johnson, "Computer-assisted detection of colonic polyps with CT colonography using neural networks and binary classification trees," Medical Physics, vol.30, no.1, pp.52-60, Jan. 2003.
31. I. Sluimer, A. Schilham, M. Prokop, and B.van Ginneken, "Computer analysis of computed tomography scans of the lung: a survey," IEEE Trans. Med. Imaging, vol.25, no.4, pp.385-405, April 2006.
32. Q. Li, "Recent progress in computer-aided diagnosis of lung nodules on thin-section CT," Comput. Med. Imaging Graph., vol.31, no.4-5, pp.248-257, June-July 2007.
33. F. Fraioli, G. Serra, and R. Passariello, "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," Radiol Med, vol.115, no.3, pp.385-402, April 2010.
34. J.M. Goo, "A computer-aided diagnosis for evaluating lung nodules on chest CT: The current status and perspective," Korean Journal of Radiology: Official Journal of the Korean Radiological Society, vol.12, no.2, pp.145-155, March-April 2011.
35. K. Suzuki, "Pixel-based machine-learning (PML) in medical imaging," Int. J. Biomedical Imaging, vol.2012, Article ID 792079, 792018 2012.
36. R.O. Duda, P.E. Hart, and D.G. Stork, in Pattern Recognit., Wiley Interscience, Hoboken, NJ, 2001.
37. C.M. Bishop, Neural Networks for Pattern Recognition, Oxford University Press, New York, 1995.
38. C.M. Bishop, "An example - character recognition," in Neural Networks for Pattern Recognition, ed. C.M. Bishop, pp.1-4, Oxford University Press, New York, 1995.
39. H.P. Chan, B. Sahiner, R.F. Wagner, and N. Petrick, "Classifier design for computer-aided diagnosis: Effects of finite sample size on the mean performance of classical and neural network classifiers," Med. Phys., vol.26, no.12, pp.2654-2668, Dec. 1999.
40. K. Fukunaga, Introduction to Statistical Pattern Recognition, Academic Press, San Diego, 1990.
41. R.E. Bellman, Adaptive control processes: A guided tour, Princeton University Press, Princeton, N.J., 1961.
42. M. Aoyama, Q. Li, S. Katsuragawa, H. MacMahon, and K. Doi, "Automated computerized scheme for distinction between benign and malignant solitary pulmonary nodules on chest images," Med. Phys., vol.29, no.5, pp.701-708, May 2002.
43. P. Pudil, J. Novovicova, and J. Kittler, "Floating search methods in feature selection," Pattern Recognit. Lett., vol.15, pp.1119-1125, 1994.
44. K. Suzuki, "Determining the receptive field of a neural filter," J Neural Eng, vol.1, no.4, pp.228-237, Dec. 2004.
45. K. Suzuki, I. Horiba, and N. Sugie, "A simple neural network pruning algorithm with application to filter synthesis," Neural Process. Lett., vol.13, no.1, pp.43-53, Feb. 2001.
46. A. Takemura, A. Shimizu, and K. Hamamoto, "Discrimination of breast tumors in ultrasonic images using an ensemble classifier based on the AdaBoost algorithm with feature selection," IEEE Trans. Med. Imaging, vol.29, no.3, pp.598-609, 2010.
47. J. Xu and K. Suzuki, "Computer-aided detection of hepatocellular carcinoma in hepatic CT: False positive reduction with feature selection," IEEE International Symposium on Biomedical Imaging (IEEE ISBI), pp.1097-1100, Chicago, IL, 2011.
48. K. Suzuki, I. Horiba, N. Sugie, and S. Ikeda, "Improvement of image quality of X-ray fluoroscopy using spatiotemporal neural filter which learns noise reduction, edge enhancement and motion compensation," Proc. Int. Conf. Signal Processing Applications and Technology (ICSPAT), pp.1382-1386, Boston, MA, 1996.
49. K. Suzuki, I. Horiba, N. Sugie, and M. Nanki, "Neural filter with selection of input features and its application to image quality improvement of medical image sequences," IEICE Trans. Inf. & Syst., vol.E85-D, no.10, pp.1710-1718, Oct. 2002.
50. K. Suzuki, I. Horiba, and N. Sugie, "Efficient approximation of neural filters for removing quantum noise from images," IEEE Trans. Signal Process., vol.50, no.7, pp.1787-1799, July 2002.
51. K. Suzuki, I. Horiba, and N. Sugie, "Neural edge enhancer for supervised edge enhancement from noisy images," IEEE Trans. Pattern Anal. Mach. Intell., vol.25, no.12, pp.1582-1596, Dec. 2003.
52. K. Suzuki, I. Horiba, N. Sugie, and M. Nanki, "Extraction of left ventricular contours from left ventriculograms by means of a neural edge detector," IEEE Trans. Med. Imaging, vol.23, no.3, pp.330-339, March 2004.
53. S.B. Lo, S.A. Lou, J.S. Lin, M.T. Freedman, M.V. Chien, and S.K. Mun, "Artificial convolution neural network techniques and applications for lung nodule detection," IEEE Trans. Med. Imaging, vol.14, no.4, pp.711-718, 1995.
54. S.C.B. Lo, H.P. Chan, J.S. Lin, H. Li, M.T. Freedman, and S.K. Mun, "Artificial convolution neural network for medical image pattern recognition," Neural Netw., vol.8, no.7-8, pp.1201-1214, 1995.
55. J.S. Lin, S.B. Lo, A. Hasegawa, M.T. Freedman, and S.K. Mun, "Reduction of false positives in lung nodule detection using a twolevel neural classification," IEEE Trans. Med. Imaging, vol.15, no.2, pp.206-217, 1996.
56. S.C. Lo, H. Li, Y. Wang, L. Kinnard, and M.T. Freedman, "A multiple circular path convolution neural network system for detection of mammographic masses," IEEE Trans. Med. Imaging, vol.21, no.2, pp.150-158, Feb. 2002.
57. B. Sahiner, H.P. Chan, N. Petrick, D. Wei, M.A. Helvie, D.D. Adler, and M.M. Goodsitt, "Classification of mass and normal breast tissue: A convolution neural network classifier with spatial domain and texture images," IEEE Trans. Med. Imaging, vol.15, no.5, pp.598-610, 1996.
58. D. Wei, R.M. Nishikawa, and K. Doi, "Application of texture analysis and shift-invariant artificial neural network to microcalcification cluster detection," Radiology, vol.201, pp.696-696, Nov. 1996.
59. W. Zhang, K. Doi, M.L. Giger, Y. Wu, R.M. Nishikawa, and R.A. Schmidt, "Computerized detection of clustered microcalcifications in digital mammograms using a shift-invariant artificial neural network," Med. Phys., vol.21, no.4, pp.517-524, April 1994.
60. K. Suzuki, S.G. Armato, 3rd, F. Li, S. Sone, and K. Doi, "Massive training artificial neural network (MTANN) for reduction of false positives in computerized detection of lung nodules in low-dose computed tomography," Med. Phys., vol.30, no.7, pp.1602-1617, July 2003.
61. K. Suzuki, H. Abe, H. MacMahon, and K. Doi, "Image-processing technique for suppressing ribs in chest radiographs by means of massive training artificial neural network (MTANN)," IEEE Trans. Med. Imaging, vol.25, no.4, pp.406-416, April 2006.
62. S. Oda, K. Awai, K. Suzuki, Y. Yanaga, Y. Funama, H. MacMahon, and Y. Yamashita, "Performance of radiologists in detection of small pulmonary nodules on chest radiographs: Effect of rib suppression with a massive-training artificial neural network," AJR. Am. J. Roentgenol., vol.193, no.5, pp.W397-W402, Nov. 2009.
63. K. Suzuki, "A supervised 'lesion-enhancement' filter by use of a massive-training artificial neural network (MTANN) in computer-aided diagnosis (CAD)," Phys. Med. Biol., vol.54, no.18, pp.S31-S45, Sept. 2009.
64. K. Suzuki, J. Shiraishi, H. Abe, H. MacMahon, and K. Doi, "Falsepositive reduction in computer-aided diagnostic scheme for detecting nodules in chest radiographs by means of massive training artificial neural network," Acad. Radiol., vol.12, no.2, pp.191-201, Feb. 2005.
65. K. Suzuki, F. Li, S. Sone, and K. Doi, "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. Imaging, vol.24, no.9, pp.1138-1150, Sept. 2005.
66. K. Suzuki, D.C. Rockey, and A.H. Dachman, "CT colonography: Advanced computer-aided detection scheme utilizing MTANNs for detection of "missed" polyps in a multicenter clinical trial," Med. Phys., vol.30, pp.2-21, 2010.
67. K. Suzuki, J. Zhang, and J. Xu, "Massive-training artificial neural network coupled with Laplacian-eigenfunction-based dimensionality reduction for computer-aided detection of polyps in CT colonography," IEEE Trans. Med. Imaging, vol.29, no.11, pp.1907-1917, Nov. 2010.
68. J. Xu and K. Suzuki, "Massive-training support vector regression and Gaussian process for false-positive reduction in computeraided detection of polyps in CT colonography," Med. Phys., vol.38, pp.1888-1902, 2011.
69. A. Jemal, R. Siegel, E. Ward, Y. Hao, J. Xu, T. Murray, and M.J. Thun, "Cancer statistics, 2008," CA. Cancer J. Clin., vol.58, no.2, pp.71-96, March-April 2008.
70. M. Kaneko, K. Eguchi, H. Ohmatsu, R. Kakinuma, T. Naruke, K. Suemasu, and N. Moriyama, "Peripheral lung cancer: Screening and detection with low-dose spiral CT versus radiography," Radiology, vol.201, no.3, pp.798-802, Dec. 1996.
71. S. Sone, S. Takashima, F. Li, Z. Yang, T. Honda, Y. Maruyama, M. Hasegawa, T. Yamanda, K. Kubo, K. Hanamura, and K. Asakura, "Mass screening for lung cancer with mobile spiral computed tomography scanner," Lancet, vol.351, no.9111, pp.1242-1245, April 1998.
72. C.I. Henschke, D.I. McCauley, D.F. Yankelevitz, D.P. Naidich, G. McGuinness, O.S. Miettinen, D.M. Libby, M.W. Pasmantier, J. Koizumi, N.K. Altorki, and J.P. Smith, "Early lung cancer action project: Overall design and findings from baseline screening," Lancet, vol.354, no.9173, pp.99-105, July 1999.
73. C.I. Henschke, D.F. Yankelevitz, D.P. Naidich, D.I. McCauley, G. McGuinness, D.M. Libby, J.P. Smith, M.W. Pasmantier, and O.S. Miettinen, "CT screening for lung cancer: suspiciousness of nodules according to size on baseline scans," Radiology, vol.231, no.1, pp.164-168, April 2004.
74. R.T. Heelan, B.J. Flehinger, M.R. Melamed, M.B. Zaman, W.B. Perchick, J.F. Caravelli, and N. Martini, "Non-small-cell lung cancer: results of the New York screening program," Radiology, vol.151, no.2, pp.289-293, May 1984.
75. M.L. Giger, K.T. Bae, and H. MacMahon, "Computerized detection of pulmonary nodules in computed tomography images," Invest. Radiol., vol.29, no.4, pp.459-465, April 1994.
76. K. Kanazawa, Y. Kawata, N. Niki, H. Satoh, H. Ohmatsu, R. Kakinuma, M. Kaneko, N. Moriyama, and K. Eguchi, "Computeraided diagnosis for pulmonary nodules based on helical CT images," Comput. Med. Imaging Graph., vol.22, no.2, pp.157-167, March-April 1998.
77. M.N. Gurcan, B. Sahiner, N. Petrick, H.P. Chan, E.A. Kazerooni, P.N. Cascade, and L. Hadjiiski, "Lung nodule detection on thoracic computed tomography images: preliminary evaluation of a computer-aided diagnosis system," Med. Phys., vol.29, no.11, pp.2552-2558, Nov. 2002.
78. Y. Lee, T. Hara, H. Fujita, S. Itoh, and T. Ishigaki, "Automated detection of pulmonary nodules in helical CT images based on an improved template-matching technique," IEEE Trans. Med. Imaging, vol.20, no.7, pp.595-604, July 2001.
79. K. Suzuki and K. Doi, "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., vol.12, no.10, pp.1333-1341, Oct. 2005.
80. H.P. Chan, B. Sahiner, R.F. Wagner, and N. Petrick, "Classifier design for computer-aided diagnosis: effects of finite sample size on the mean performance of classical and neural network classifiers," Med. Phys, vol.26, no.12, pp.2654-2668, Dec. 1999.
81. B. Sahiner, H.P. Chan, and L. Hadjiiski, "Classifier performance prediction for computer-aided diagnosis using a limited dataset," Med. Phys, vol.35, no.4, pp.1559-1570, April 2008.
82. A.A. Farag, A. El-Baz, G. Gimelfarb, M.A. El-Ghar, and T. Eldiasty, "Quantitative nodule detection in low dose chest CT scans: new template modeling and evaluation for CAD system design," Medical image computing and computer-assisted intervention: MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention, vol.8, no. Pt 1, pp.720-728, 2005.
83. Z. Ge, B. Sahiner, H.P. Chan, L.M. Hadjiiski, P.N. Cascade, N. Bogot, E.A. Kazerooni, J. Wei, and C. Zhou, "Computer-aided detection of lung nodules: false positive reduction using a 3D gradient field method and 3D ellipsoid fitting,"Med. Phys., vol.32, no.8, pp.2443-2454, Aug. 2005.
84. S. Matsumoto, H.L. Kundel, J.C. Gee, W.B. Gefter, and H. Hatabu, "Pulmonary nodule detection in CT images with quantized convergence index filter," Med. Image Anal., vol.10, no.3, pp.343-352, June 2006.
85. R. Yuan, P.M. Vos, and P.L. Cooperberg, "Computer-aided detection in screening CT for pulmonary nodules," AJR. Am. J. Roentgenol., vol.186, no.5, pp.1280-1287, May 2006.
86. J. Bi, S. Periaswamy, K. Okada, T. Kubota, G. Fung, M. Salganicoff, and R.B. Rao, "Computer aided detection via asymmetric cascade of sparse hyperplane classifiers," Proc. ACM SIGKDD, pp.837-844, 2006.
87. J. Pu, B. Zheng, J.K. Leader, X.H. Wang, and D. Gur, "An automated CT based lung nodule detection scheme using geometric analysis of signed distance field," Med. Phys., vol.35, no.8, pp.3453-3461, Aug. 2008.
88. A. Retico, P. Delogu, M.E. Fantacci, I. Gori, and A. Preite Martinez, "Lung nodule detection in low-dose and thin-slice computed tomography," Computers in Biology and Medicine, vol.38, no.4, pp.525-534, April 2008.
89. X. Ye, X. Lin, J. Dehmeshki, G. Slabaugh, and G. Beddoe, "Shapebased computer-aided detection of lung nodules in thoracic CT images," IEEE Trans. Biomed. Eng., vol.56, no.7, pp.1810-1820, July 2009.
90. B. Golosio, G.L. Masala, A. Piccioli, P. Oliva, M. Carpinelli, R. Cataldo, P. Cerello, F. De Carlo, F. Falaschi, M.E. Fantacci, G. Gargano, P. Kasae, and M. Torsello, "A novel multithreshold method for nodule detection in lung CT," Med. Phys., vol.36, no.8, pp.3607-3618, Aug. 2009.
91. S.G. Armato, 3rd, G. McLennan, M.F. McNitt-Gray, C.R. Meyer, D. Yankelevitz, D.R. Aberle, C.I. Henschke, E.A. Hoffman, E.A. Kazerooni, H. MacMahon, A.P. Reeves, B.Y. Croft, and L.P. Clarke, "Lung image database consortium: developing a resource for the medical imaging research community," Radiology, vol.232, no.3, pp.739-748, Sept. 2004.
92. K. Murphy, B. van Ginneken, A.M. Schilham, B.J. de Hoop, H.A. Gietema, and M. Prokop, "A large-scale evaluation of automatic pulmonary nodule detection in chest CT using local image features and k-nearest-neighbour classification," Med. Image Anal., vol.13, no.5, pp.757-770, Oct. 2009.
93. M. Tan, R. Deklerck, B. Jansen, M. Bister, and J. Cornelis, "A novel computer-aided lung nodule detection system for CT images," Med. Phys., vol.38, no.10, pp.5630-5645, Oct. 2011.
94. T. Messay, R.C. Hardie, and S.K. Rogers, "A new computationally efficient CAD system for pulmonary nodule detection in CT imagery," Med. Image Anal., vol.14, no.3, pp.390-406, June 2010.
95. A. Riccardi, T.S. Petkov, G. Ferri, M. Masotti, and R. Campanini, "Computer-aided detection of lung nodules via 3D fast radial transform, scale space representation, and Zernike MIP classification," Med. Phys., vol.38, no.4, pp.1962-1971, April 2011.
96. R.B. Rao, J. Bi, G. Fung, M. Salganicoff, N. Obuchowski, and D. Naidich, "LungCAD: A clinically approved, machine learning system for lung cancer detection," Proc. ACMSIGKDD, pp.1033-1037, 2007.
97. B. Sahiner, H.P. Chan, N. Petrick, R.F. Wagner, and L. Hadjiiski, "Feature selection and classifier performance in computer-aided diagnosis: the effect of finite sample size," Med. Phys., vol.27, no.7, pp.1509-1522, July 2000.
98. F. Li, S. Sone, H. Abe, H. MacMahon, S.G. Armato, 3rd, and K. Doi, "Lung cancers missed at low-dose helical CT screening in a general population: comparison of clinical, histopathologic, and imaging findings," Radiology, vol.225, no.3, pp.673-683, Dec. 2002.
99. S.J. Swensen, J.R. Jett, T.E. Hartman, D.E. Midthun, J.A. Sloan, A.M. Sykes, G.L. Aughenbaugh, and M.A. Clemens, "Lung cancer screening with CT: Mayo Clinic experience," Radiology, vol.226, no.3, pp.756-761, March 2003.
100. C.E. Metz, "ROC methodology in radiologic imaging," Invest. Radiol., vol.21, no.9, pp.720-733, Sept. 1986.
101. J.A. Hanley and B.J. McNeil, "A method of comparing the areas under receiver operating characteristic curves derived from the same cases," Radiology, vol.148, no.3, pp.839-843, Sept. 1983.
102. Y. Kawata, N. Niki, H. Ohmatsu, R. Kakinuma, K. Eguchi, M. Kaneko, and N. Moriyama, "Quantitative surface characterization of pulmonary nodules based on thin-section CT images," IEEE Trans. Nucl. Sci., vol.45, no.4, pp.2132-2138, 1998.
103. M.F. McNitt-Gray, E.M. Hart, N. Wyckoff, J.W. Sayre, J.G. Goldin, and D.R. Aberle, "A pattern classification approach to characterizing solitary pulmonary nodules imaged on high resolution CT: Preliminary results," Med. Phys., vol.26, no.6, pp.880-888, June 1999.
104. Y. Matsuki, K. Nakamura, H. Watanabe, T. Aoki, H. Nakata, S. Katsuragawa, and K. Doi, "Usefulness of an artificial neural network for differentiating benign from malignant pulmonary nodules on high-resolution CT: Evaluation with receiver operating characteristic analysis," AJR. Am. J. Roentgenol., vol.178, no.3, pp.657-663, March 2002.
105. K. Mori, N. Niki, T. Kondo, Y. Kamiyama, T. Kodama, Y. Kawada, and N. Moriyama, "Development of a novel computer-aided diagnosis system for automatic discrimination of malignant from benign solitary pulmonary nodules on thin-section dynamic computed tomography," J. Comput. Assist. Tomogr., vol.29, no.2, pp.215-222, March-April 2005.
106. S.K. Shah, M.F. McNitt-Gray, S.R. Rogers, J.G. Goldin, R.D. Suh, J.W. Sayre, I. Petkovska, H.J. Kim, and D.R. Aberle, "Computer aided characterization of the solitary pulmonary nodule using volumetric and contrast enhancement features," Academic Radiology, vol.12, no.10, pp.1310-1319, Oct. 2005.
107. S. Iwano, T. Nakamura, Y. Kamioka, M. Ikeda, and T. Ishigaki, "Computer-aided differentiation of malignant from benign solitary pulmonary nodules imaged by high-resolution CT," Comput. Med. Imaging Graph., vol.32, no.5, pp.416-422, July 2008.
108. T.W. Way, B. Sahiner, H.P. Chan, L. Hadjiiski, P.N. Cascade, A. Chughtai, N. Bogot, and E. Kazerooni, "Computer-aided diagnosis of pulmonary nodules on CT scans: improvement of classification performance with nodule surface features," Med. Phys., vol.36, no.7, pp.3086-3098, July 2009.
109. H. Chen, Y. Xu, Y. Ma, and B. Ma, "Neural network ensemblebased computer-aided diagnosis for differentiation of lung nodules on CT images: clinical evaluation," Acad. Radiol., vol.17, no.5, pp.595-602, May 2010.
110. M.C. Lee, L. Boroczky, K. Sungur-Stasik, A.D. Cann, A.C. Borczuk, S.M. Kawut, and C.A. Powell, "Computer-aided diagnosis of pulmonary nodules using a two-step approach for feature selection and classifier ensemble construction," Artificial Intelligence in Medicine, vol.50, no.1, pp.43-53, Sept. 2010.
111. Y. Kawata, N. Niki, H. Ohmatsu, and N. Moriyama, "Examplebased assisting approach for pulmonary nodule classification in three-dimensional thoracic computed tomography images," Acad. Radiol., vol.10, no.12, pp.1402-1415, Dec. 2003.
112. Y. Kawata, N. Niki, H. Ohmatsu, M. Kusumoto, T. Tsuchida, K. Eguchi, M. Kaneko, and N. Moriyama, "Quantitative classification based on CT histogram analysis of non-small cell lung cancer: correlation with histopathological characteristics and recurrence-free survival," Med. Phys., vol.39, no.2, pp.988-1000, Feb. 2012.
113. H. Abe, H. MacMahon, R. Engelmann, Q. Li, J. Shiraishi, S. Katsuragawa, M. Aoyama, T. Ishida, K. Ashizawa, C.E. Metz, and K. Doi, "Computer-aided diagnosis in chest radiography: Results of large-scale observer tests at the 1996-2001 RSNA scientific assemblies," Radiographics, vol.23, no.1, pp.255-265, Jan.-Feb. 2003.
114. A. Jemal, T. Murray, E. Ward, A. Samuels, R.C. Tiwari, A. Ghafoor, E.J. Feuer, and M.J. Thun, "Cancer statistics, 2005," CA: A Cancer Journal for Clinicians, vol.55, no.1, pp.10-30, Jan.-Feb. 2005.
115. S.J. Winawer, R.H. Fletcher, L. Miller, F. Godlee, M.H. Stolar, C.D. Mulrow, S.H. Woolf, S.N. Glick, T.G. Ganiats, J.H. Bond, L. Rosen, J.G. Zapka, S.J. Olsen, F.M. Giardiello, J.E. Sisk, R. Van Antwerp, C. Brown-Davis, D.A. Marciniak, and R.J. Mayer, "Colorectal cancer screening: clinical guidelines and rationale," Gastroenterology, vol.112, no.2, pp.594-642, Feb. 1997.
116. K. Suzuki and A.H. Dachman, "Computer-aided diagnosis in CT colonography," in Atlas of Virtual Colonoscopy, eds. A.H. Dachman and A. Laghi, pp.163-182, Springer, New York, 2011.
117. H. Yoshida and J. Näppi, "Three-dimensional computer-aided diagnosis scheme for detection of colonic polyps," IEEE Trans. Med. Imaging, vol.20, no.12, pp.1261-1274, Dec. 2001.
118. R.M. Summers, C.D. Johnson, L.M. Pusanik, J.D. Malley, A.M. Youssef, and J.E. Reed, "Automated polyp detection at CT colonography: Feasibility assessment in a human population," Radiology, vol.219, no.1, pp.51-59, April 2001.
119. D.S. Paik, C.F. Beaulieu, G.D. Rubin, B. Acar, R.B. Jeffrey, Jr., J. Yee, J. Dey, and S. Napel, "Surface normal overlap: a computeraided detection algorithm with application to colonic polyps and lung nodules in helical CT," IEEE Trans. Med. Imaging, vol.23, no.6, pp.661-675, June 2004.
120. G. Kiss, J. Van Cleynenbreugel, M. Thomeer, P. Suetens, and G. Marchal, "Computer-aided diagnosis in virtual colonography via combination of surface normal and sphere fitting methods," Eur Radiol, vol.12, no.1, pp.77-81, Jan. 2002.
121. S.B. Gokturk, C. Tomasi, B. Acar, C.F. Beaulieu, D.S. Paik, R.B. Jeffrey, Jr., J. Yee, and S. Napel, "A statistical 3-D pattern processing method for computer-aided detection of polyps in CT colonography," IEEE Trans. Med. Imaging, vol.20, no.12, pp.1251-1260, Dec. 2001.
122. J. Nappi and H. Yoshida, "Automated detection of polyps with CT colonography: Evaluation of volumetric features for reduction of false-positive findings," Acad. Radiol., vol.9, no.4, pp.386-397, April 2002.
123. B. Acar, C.F. Beaulieu, S.B. Gokturk, C. Tomasi, D.S. Paik, R.B. Jeffrey, Jr., J. Yee, and S. Napel, "Edge displacement field-based classification for improved detection of polyps in CT colonography," IEEE Trans. Med. Imaging, vol.21, no.12, pp.1461-1467, Dec. 2002.
124. A.K. Jerebko, J.D. Malley, M. Franaszek, and R.M. Summers, "Multiple neural network classification scheme for detection of colonic polyps in CT colonography data sets," Academic Radiology, vol.10, no.2, pp.154-160, Feb. 2003.
125. A.K. Jerebko, J.D. Malley, M. Franaszek, and R.M. Summers, "Support vector machines committee classification method for computer-aided polyp detection in CT colonography," Academic Radiology, vol.12, no.4, pp.479-486, April 2005.
126. Z. Wang, Z. Liang, L. Li, X. Li, B. Li, J. Anderson, and D. Harrington, "Reduction of false positives by internal features for polyp detection in CT-based virtual colonoscopy," Med. Phys., vol.32, no.12, pp.3602-3616, Dec. 2005.
127. K. Suzuki, H. Yoshida, J. Nappi, and A.H. Dachman, "Massivetraining artificial neural network (MTANN) for reduction of false positives in computer-aided detection of polyps: Suppression of rectal tubes," Med. Phys., vol.33, no.10, pp.3814-3824, Oct. 2006.
128. J. Li, R. Van Uitert, J. Yao, N. Petrick, M. Franaszek, A. Huang, and R.M. Summers, "Wavelet method for CT colonography computer-aided polyp detection," Med. Phys., vol.35, no.8, pp.3527-3538, Aug. 2008.
129. S. Wang, J. Yao, and R.M. Summers, "Improved classifier for computer-aided polyp detection in CT colonography by nonlinear dimensionality reduction," Med. Phys., vol.35, no.4, pp.1377-1386, April 2008.
130. J. Yao, J. Li, and R.M. Summers, "Employing topographical height map in colonic polyp measurement and false positive reduction," Pattern Recognit., vol.42, no.6, pp.1029-1040, 2009.
131. T. Doshi, D. Rusinak, R.A. Halvorsen, D.C. Rockey, K. Suzuki, and A.H. Dachman, "CT colonography: False-negative interpretations," Radiology, vol.244, no.1, pp.165-173, July 2007.
132. D.C. Rockey, E. Paulson, D. Niedzwiecki, W. Davis, H.B. Bosworth, L. Sanders, J. Yee, J. Henderson, P. Hatten, S. Burdick, A. Sanyal, D.T. Rubin, M. Sterling, G. Akerkar, M.S. Bhutani, K. Binmoeller, J. Garvie, E.J. Bini, K. McQuaid, W.L. Foster, W.M. Thompson, A. Dachman, and R. Halvorsen, "Analysis of air contrast barium enema, computed tomographic colonography, and colonoscopy: Prospective comparison," Lancet, vol.365, no.9456, pp.305-311, Jan. 2005.
133. H. Zhu, Z. Liang, P.J. Pickhardt, M.A. Barish, J. You, Y. Fan, H. Lu, E.J. Posniak, R.J. Richards, and H.L. Cohen, "Increasing computer-aided detection specificity by projection features for CT colonography," Med. Phys., vol.37, no.4, pp.1468-1481, April 2010.
134. S. Wang, J. Yao, N. Petrick, and R.M. Summers, "Combining statistical and geometric features for colonic polyp detection in CTC based on multiple kernel learning," Int. J. Computational Intelligence and Applications, vol.9, no.1, pp.1-15, Jan. 2010.