False-positive reduction in computer-aided diagnostic scheme for detecting nodules in chest radiographs by means of massive training artificial neural network

Academic Radiology

Volumn 12, Issue 2, 2005, Pages 191-201

  Suzuki, Kenji ^a   Shiraishi, Junji ^a   Abe, Hiroyuki ^a   MacMahon, Heber ^a   Doi, Kunio ^a  

^a UNIVERSITY OF CHICAGO   (United States)

Author keywords

Artificial neural network; Cancer; Chest radiography; Computer aided diagnosis; Lung nodule

Indexed keywords

ARTICLE; ARTIFICIAL NEURAL NETWORK; COMPUTER AIDED DESIGN; DIAGNOSTIC PROCEDURE; FILTER; HUMAN; LABORATORY DIAGNOSIS; LUNG NODULE; PRIORITY JOURNAL; RADIOLOGIST; REDUCTION; THORAX RADIOGRAPHY;

EID: 13944267171     PISSN: 10766332     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.acra.2004.11.017     Document Type: Article

References (49)

1. R.T. Heelan, B.J. Flehinger, M.R. Melamed Non-small-cell lung cancer results of the New York screening program Radiology 151 1984 289 293
2. T. Sobue, R. Suzuki, M. Matsuda Survival for clinical stage I lung cancer not surgically treated Cancer 69 1992 685 692
3. J.H.M. Austin, B.M. Romney, L.S. Goldsmith Missed bronchogenic carcinoma radiographic findings in 27 patients with a potentially resectable lesion evident in retrospect Radiology 182 1992 115 122
4. P.K. Shah, J.H.M. Austin, C.S. White Missed non-small cell lung cancer radiographic findings of potentially resectable lesions evident only in retrospect Radiology 226 2003 235 241
5. H. MacMahon, K. Doi, H.P. Chan Computer-aided diagnosis in the chest J Thoracic Imaging 5 1990 67 76
6. K. Abe, K. Doi, H. MacMahon Computer-aided diagnosis in chest radiography analysis of results in a large clinical series Invest Radiol 28 1993 987 993
7. T. Kobayashi, X.W. Xu, H. MacMahon Effect of a computer-aided diagnosis scheme on radiologists' performance in detection of lung nodules on radiographs Radiology 199 1996 843 848
8. B.V. Ginneken, B.T.H. Romeny, M.A. Viergever Computer-aided diagnosis in chest radiography a survey IEEE Trans Med Imag 20 2001 1228 1241
9. M.L. Giger, K. Doi, H. MacMahon Image feature analysis and computer-aided diagnosis in digital radiography. 3. Automated detection of nodules in peripheral lung fields Med Phys 15 1988 158 166
10. M.L. Giger, K. Doi, H. MacMahon Pulmonary nodules computer-aided detection in digital chest images Radiographics 10 1990 41 51
11. Y. Wu, K. Doi, M.L. Giger Reduction of false positives in computerized detection of lung nodules in chest radiographs using artificial neural networks, discriminant analysis, and a rule-based scheme J Digital Imag 7 1994 196 207
12. X.W. Xu, K. Doi, T. Kobayashi Development of an improved CAD scheme for automated detection of lung nodules in digital chest images Med Phys 24 1997 1395 1403
13. Q. Li, S. Katsuragawa, K. Doi Computer-aided diagnostic scheme for pulmonary nodule detection in digital chest radiographs elimination of false-positives by using a multiple-templates matching technique Med Phys 28 2001 2070 2076
14. P. Sankar, J.A. Sklansky Gestalt guided heuristic boundary follower for X-ray images of lung nodules IEEE Trans Pattern Anal Machine Intell 4 1982 326 331
15. S.C. Lo, Sl Lou, J.S. Lin Artificial convolution neural network techniques and applications for lung nodule detection IEEE Trans Med Imag 14 1995 711 718
16. J.S. Lin, A. Hasegawa, M. Freedman Differentiation between nodules and end-on vessels using a convolution neural network architecture J Digital Imag 8 1995 132 141
17. J.S. Lin, S.C. Lo, A. Hasegawa Reduction of false positives in lung nodule detection using a two-level neural classification IEEE Trans Med Imag 15 1996 206 217
18. M.J. Carreira, D. Cabello, M.G. Penedo Computer-aided diagnosis automatic detection of lung nodules Med Phys 25 1998 1998 2006
19. M.G. Penedo, M.J. Carreira, A. Mosquera Computer-aided diagnosis a neural-network-based approach to lung nodule detection IEEE Trans Med Imag 17 1998 872 880
20. G. Coppini, S. Diciotti, M. Falchini Neural networks for computer-aided diagnosis detection of lung nodules in chest radiograms IEEE Trans Inform Technol Biomed 7 2003 344 357
21. W. Lampeter, J. Wandtke Computerized search of chest radiographs for nodules Invest Radiol 21 1986 384 390
22. C. Floyd Jr, E. Patz, J. Lo Diffuse nodular lung disease on chest radiographs a pilot study of characterization by fractal dimension AJR Am J Roentgenol 167 1996 1185 1187
23. F. Mao, W. Qian, J. Gaviria Fragmentary window filtering for multiscale lung nodule detection preliminary study Acad Radiol 5 1998 306 311
24. S. Kakeda, J. Moriya, H. Sato Improved detection of lung nodules on chest radiographs using a commercial computer-aided diagnosis system AJR Am J Roentgenol 182 2004 505 510
25. T. Matsumoto, H. Yoshimura, K. Doi Image feature analysis of false-positive diagnoses produced by automated detection of lung nodules Invest Radiol 27 1992 587-579
26. J. Shiraishi, S. Katsuragawa, J. Ikezoe Development of a digital image database for chest radiographs with and without a lung nodule ROC analysis on radiologists' performance in detection of pulmonary nodules AJR Am J Roentgenol 174 2000 71 74
27. J. Shiraishi, H. Abe, R. Engelmann Characteristics of image database on the performance of computer-aided diagnosis for the detection of pulmonary nodules in chest radiographs Proc SPIE Med Imag 5032 2003 177 182
28. K. Suzuki, I. Horiba, N. Sugie Neural filter with selection of input features and its application to image quality improvement of medical image sequences IEICE Trans Inform Syst E85-D 2002 1710 1718
29. K. Suzuki, I. Horiba, N. Sugie Neural edge detector-a good mimic of conventional one yet robuster against noise Lect Notes Comput Sci 2085 2001 303 310
30. K. Suzuki, I. Horiba, N. Sugie Neural edge enhancer for supervised edge enhancement from noisy images IEEE Trans Pattern Anal Machine Intell 25 2003 1582 1596
31. K. Suzuki, I. Horiba, N. Sugie Extraction of left ventricular contours from left ventriculograms by means of a neural edge detector IEEE Trans Med Imag 23 2004 330 339
32. K. Suzuki, I. Horiba, N. Sugie Training under achievement quotient criterion Neural Networks Signal Proc 10 2000 537 546
33. K. Suzuki, I. Horiba, N. Sugie Simple unit-pruning with gain-changing training Neural Networks Signal Proc 11 2001 153 162
34. K. Suzuki, I. Horiba, N. Sugie Designing the optimal structure of a neural filter Neural Networks Signal Proc 8 1998 323 332
35. K. Suzuki, I. Horiba, N. Sugie A simple neural network pruning algorithm with application to filter synthesis Neural Proc Lett 13 2001 43 53
36. K. Suzuki, I. Horiba, N. Sugie Efficient approximation of a neural filter for quantum noise removal in X-ray images IEEE Trans Signal Proc 50 2002 1787 1799
37. K. Suzuki, S.G. Armato III, F. Li Massive training artificial neural network (MTANN) for reduction of false positives in computerized detection of lung nodules in low-dose CT Med Phys 30 2003 1602 1617
38. K. Suzuki, S.G. Armato III, F. Li Effect of a small number of training cases on the performance of massive training artificial neural network (MTANN) for reduction of false positives in computerized detection of lung nodules in low-dose CT Proc SPIE Medical Imaging (SPIE MI) 5032 2003 1355 1366
39. K. Suzuki, I. Horiba, K. Ikegaya Recognition of coronary arterial stenosis using neural network on DSA system Systems and Computers in Japan 26 1995 66 74
40. K. Suzuki, I. Horiba, N. Sugie Computer-aided diagnosis system for coronary artery stenosis using a neural network Proc SPIE Med Imag 4322 2001 1771 1782
41. S. Katsuragawa, K. Doi, N. Nakamori Image feature analysis and computer-aided diagnosis in digital radiography Effect of digital parameters on the accuracy of computerized analysis of interstitial disease in digital chest radiographs Med Phys 17 1990 72 78
42. D.E. Rumelhart, G.E. Hinton, R.J. Williams Learning representations of back-propagation errors Nature 323 1986 533 536
43. the PDP Research Group D.E. Rumelhart, G.E. Hinton, R.J. Williams Learning internal representations by error propagation D.E. Rumelhart J.L. McClelland Parallel Distributed Processing 1 1986 MIT Press Cambridge, MA 318 362
44. D.P. Chakraborty, L.H.L. Winter Free-response methodology alternate analysis and a new observer-performance experiment Radiology 174 1990 873 881
45. K. Funahashi On the approximate realization of continuous mappings by neural networks Neural Networks 2 1989 183 192
46. A.R. Barron Universal approximation bounds for superpositions of a sigmoidal function IEEE Trans Inform Theor 39 1993 930 945
47. C.E. Metz ROC methodology in radiologic imaging Invest Radiol 21 1986 720 733
48. C.E. Metz, B.A. Herman, J.H. Shen Maximum likelihood estimation of receiver operating characteristic (ROC) curves from continuously-distributed data Stat Med 17 1998 1033 1053
49. J.A. Hanley, B.J. McNeil A method of comparing the areas under receiver operating characteristic curves derived from the same cases Radiology 148 1983 839 843