Computer-aided detection and classification of microcalcifications in mammograms: A survey

Pattern Recognition

Volumn 36, Issue 12, 2003, Pages 2967-2991

  Cheng, H D ^a   Cai, Xiaopeng ^a   Chen, Xiaowei ^a   Hu, Liming ^a   Lou, Xueling ^a  

^a Utah State University ^*  (United States)

Author keywords

Computer aided detection; Contrast enhancement; False negative (FN); False positive (FP); Features extraction; Free response receiver operating characteristic (FROC); Mammography; Microcalcification clusters (MCCs) detection and classification; Microcalcifications; Receiver operating characteristic (ROC); Segmentation

Indexed keywords

ALGORITHMS; COMPUTER AIDED DIAGNOSIS; MAMMOGRAPHY; TUMORS;

MICROCALCIFICATION CLUSTERS (MCC);

PATTERN RECOGNITION;

IMAGE CLASSIFICATION;

EID: 0142120449     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0031-3203(03)00192-4     Document Type: Article

References (186)

1. Zhou X. Gordon R. Detection of early breast cancer: An overview and future prospects Crit. Rev. Biomed. Eng. 17 1989 203-255
2. Chan H.P. Doi K. Vyborny C.J. Lam K.L. Schmidt R.A. Computer-aided detection of microcalcifications in mammograms-methodology and preliminary clinical study Invest. Radiol. 23 9 1988 664-671
3. Chan H.P. Doi K. Galhotra S. Vyborny C.J. MacMahon H. Jokich P.M. Image feature analysis and computer-aided diagnosis in digital radiography I. Automated detection of microcalcifications in mammography Med. Phys. 14 4 1987 538-548
4. Wu Y. Doi K. Giger M.L. Nishikawa R.M. Computer-aided detection of microcalcifications in digital mammograms Invest. Radiol. 9 1988 664-674
5. Davies D.H. Dance D.R. The automatic computer detection of subtle calcifications in radiographically dense breasts Phys. Med. Biol. 37 1992 1385-1390
6. Lee S. Lo C. Wang C. Chung P. Chang C. Yang C. Hsu P. A computer-aided design mammography screening system for detection and classification of microcalcifications Int. J. Med. Inform. 60 1 2000 29-57
7. Yu S. Guan L. A CAD system for the automatic detection of clustered microcalcifications in digitized mammogram films IEEE Trans. Med. Imag. 19 2 2000 115-126
8. Verma B. Zakos J. A computer-aided diagnosis system for digital mammograms based on fuzzy-neural and feature extraction techniques IEEE Trans. Inform. Technol. Biomed. 5 1 2001 46-54
9. Yoshida H. Doi K. Nishikawa R.M. Giger M.L. Schmidt R.A. An improved computer-assisted diagnostic scheme using wavelet transform for detecting clustered microcalcifications in digital mammograms Acad. Radiol. 3 8 1996 621-627
10. Zheng B. Chang Y. Staiger M. Good W. Gur D. Computer-aided detection of clustered microcalcifications in digitized mammograms Acad. Radiol. 2 1995 655-662
11. Wilson M. Mitra S. Roberson G.H. Shieh Y.Y. Automated microcalcification detection in mammograms using statistical-variable box-threshold filter method SPIE 3165 1997 195-326
12. M.A. Gavrielides, J.Y. Lo, Jr CE, Parameter optimization of a computer-aided diagnosis scheme for the segmentation of microcalcification clusters in mammograms, Med. Phys. 29(4) (2002) 475-483.
13. Papadopoulos A. Fotiadis D.I. Likas A. An automatic microcalcification detection system based on a hybrid neural network classifier Artif. Intell. Med. 25 2 2002 149-167
14. Verma B. Zakos J. A computer-aided diagnosis system for digital mammograms based on fuzzy-neural and feature extraction techniques IEEE Trans. Inform. Technol. Biomed. 5 1 2001 46-54
15. Leichter I. Lederman R. Buchbinder S. Bamberger P. Novak B. Fields S. Optimizing parameters for computer-aided diagnosis of microcalcifications at mammography Acad. Radiol. 7 6 2000 406-412
16. Nishikawa R.M. Detection of microcalcification Karssemeijer N. Thijssen M. Hendriks J. van Erning L. Digital Mammography Nijmegen 98 1998 131-153 Kluwer Academic Publisher Amsterdam
17. Olson S.L. Fam B.W. Winter P.F. Scholz F.J. Lee A.K. Gordon S.E. Breast calcifications: Analysis of imaging properties Radiology 169 2 1988 329-332
18. Dhawan A.P. Royer E.L. Mammographic feature enhancement by computerized image processing Comput. Methods Programs Biomed. 27 1 1988 23-35
19. Sickles E.A. Mammographic features of 300 consecutive nonpalpable breast cancers Am. J. Radiol. 146 1986 661-665
20. Beghdadi A. Negrate A.L. Contrast enhancement technique based on local detection of edges Comput. Vision Graphics Image Process. 46 1989 162-174
21. Dengler J. Behrens S. Desaga J.F. Segmentation of microcalcifications in mammograms IEEE Trans. Med. Imag. 12 4 1993 634-642
22. H.D. Cheng, H.J. Xu, Fuzzy approach to contrast enhancement, 14th International Conference on Pattern Recognition, Brisbane, Australia, August 1998, pp. 17-22.
23. N. Karssemeijer, Adaptive noise equalization and image analysis in mammography, Information Processing in Medical Imaging: 13th International Conference, IPMI '93, AZ, USA, 1993, pp. 472-486.
24. McSweeney M.B. Sprawls P. Egan R.L. Enhanced image mammography AJR 140 1983 9-14
25. Chan H.P. Vyborny C.J. McaMahon H. Metz C.E. Doi K. Sickles E.A. Digital mammography: ROC studies of the effects of pixel size and unsharp-mask filtering on the detection of subtle microcalcifications Invest. Radiol. 22 7 1987 581-589
26. Woods K. Clarke L.P. Velthuizen R. Enhancement of digital mammograms using a local thresholding technique Annual International Conference of the IEEE Engineering in Medicine and Biology Society 13 1 1991 114-115
27. Gordon R. Rangayyan R.M. Feature enhancement of film mammograms using fixed and adaptive neighborhoods Appl. Opt. 23 4 1984 560-564
28. Dhawan A.P. Buelloni G. Gordon R. Enhancement of mammographic features by optimal adaptive neighborhood image processing IEEE Trans. Med. Imag. MI-5 1 1986 8-15
29. Morrow W.M. Paranjape R.B. Rangayyan R.M. Desautels J.E.L. Region-based contrast enhancement of mammograms IEEE Trans. Med. Imag. 11 3 1992 392-406
30. Kallergi M. Woods K. Clarke L.P. Qian W. Clark R.A. Image segmentation in digital mammography: Comparison of local thresholding and region growing algorithms Comput. Med. Imag. Graph. 16 1992 323-331
31. Woods K.S. Doss C.C. Bowyer K.W. Solka J.L. Priebe C.E. Kegelmeyer W.P. Comparative evaluation of pattern recognition techniques for detection of microcalcifications in mammography Int. J. Pattern Recognition Artif. Intell. 7 1993 1417-1436
32. Shen L. Rangayyan R. Desautles J.E.L. Detection and classification of mammographic calcifications Int. J. Pattern Recognition Artif. Intell. 7 1993 1403-1416
33. Shen L. Rangayyan R.M. Desautels J.E.L. Application of shape analysis to mammographic calcifications IEEE Trans. Med. Imag. 13 2 1994 263-274
34. Gurcan M.N. Yardimci Y. Cetin A.E. Ansari R. Detection of microcalcifications in mammograms using higher order statistics Signal Process. Lett. 4 8 1997 213-216
35. M.N. Gurcan, Y. Yardimci, A.E. Cetin, R. Ansari, Automated detection and enhancement of microcalcifications in mammograms using nonlinear subband decomposition, 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing, Vol. 4, Munich, Germany, April 1997, pp. 3069-2072.
36. Cheng H.D. Lui Y.M. Freimanis R.I. A novel approach to microcalcification detection using fuzzy logic technique IEEE Trans. Med. Imag. 17 3 1998 442-450
37. Laine A.F. Schuler S. Fan J. Huda W. Mammographic feature enhancement by multiscale analysis IEEE Trans. Med. Imag. 13 4 1994 7250-7260
38. Kim J.K. Park J.M. Song K.S. Park H.W. Adaptive mammographic image enhancement using first derivative and local statistics IEEE Trans. Med. Imaging. 16 5 1997 495-502
39. Kim J.K. Park J.M. Song S.S. Park H.W. Detection of clustered microcalcifications on mammograms using surrounding region dependence method and artificial neural network J. VLSI Signal Process. 18 1998 251-262
40. Kim J.K. Park H.W. Statistical textural features for detection of microcalcifications in digitized mammograms IEEE Trans. Med. Imag. 18 3 1999 231-238
41. Li H. Ray Liu K.J. Lo S.C.B. Fractal modeling and segmentation for the enhancement of microcalcifications in digital mammograms IEEE Trans. Med. Imag. 16 6 1997 785-798
42. H. Li, K.J.R. Liu, S.C.B. Lo, Fractal modeling of mammogram and enhancement of microcalcifications, 1996 IEEE Nuclear Science Symposium - Medical Imaging Conference, Vol. 3, 1996, pp. 1850-1854.
43. S.H. Nam, J.Y. Choi, A methods of image enhancement and fractal dimension for detection of microcalcifications in mammogram, Proceedings of the 20th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Vol. 20 (2), 1998, pp. 1009-1012.
44. S. Yu, S. Brown, Y. Xue, L. Guan, Enhancement and identification of microcalcifications in mammogram images using wavelets, 1996 IEEE International Conference on Systems, Man and Cybernetics, Vol. 2, Beijing China, October 1996, pp. 1166-1171.
45. Wang T.C. Karayiannis N.B. Detection of microcalcifications in digital mammograms using wavelets IEEE Trans. Med. Imag. 17 4 1998 498-509
46. Zheng B. Qian W. Clarke L.P. Digital mammography: mixed feature neural network with spectral entropy decision for detection of microcalcifications IEEE Trans. Med. Imag. 15 5 1996 589-597
47. H. Yoshida, K. Doi, R.M. Nishikawa, Automated detection of clustered microcalcifications, SPIE Image Processing, Vol. 2167, Newport Beach, CA, February 1994, pp. 868-886.
48. Mascio L.N. Hernandez J.M. Logan C.M. Automated analysis for microcalcifications in high resolution digital mammograms SPIE Image Process. 1898 1993 472-479
49. Cheng H. Lui Y. Freimanis R. A novel approach to microcalcification detection using fuzzy logic technique IEEE Trans. Med. Imag. 17 3 1998
50. Lefebvre F. Benali H. Kahn E. Paola R.D. A fractal approach to the segmentation of microcalcifications in digital mammograms Med. Phys. 22 4 1995 381-391
51. Davies D.H. Dance D.R. Automatic computer detection of clustered calcifications in digital mammograms Phys. Med. Biol. 35 1990 1111-1118
52. Bankman I.N. Nizialek T. Simon I. Gatewood O.B. Weinberg I.N. Brody W.R. Segmentation algorithms for detecting microcalcifications in mammograms IEEE Trans. Med. Imag. 1 2 1997 141-149
53. Kass M. Witken A. Terzopoulos D. Snakes: Active contour models Int. J. Comput. Vision 1 4 1988 321-331
54. J.M. Mossi, A. Albiol, Improving detection of clustered microcalcifications using morphological connected operators, 1999 IEEE Image Processing and its Applications, 1999, pp. 498-501.
55. R.M. Nishikawa, Y. Jiang, M.L. Giger, K. Doi, C.J. Vyborny, R.A. Schmidt, Computer-aided detection of clustered microcalcifications, Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, 1992, pp. 1375-1378.
56. D. Zhao, M. Shridhar, D.G. Daul, Morphology on detection of calcifications in mammograms, 1992 IEEE International Conference on Acoustics, Speech and Signal Processing, III, March 23-26, 1992, pp. 129-132.
57. Jin H.R. Extraction of microcalcifications from mammograms using morphological filter with multiple structuring elements System Comput. Jpn. 24 11 1993 66-74
58. Chen C.H. Lee G.G. On digital mammogram segmentation and microcalcification detection using multiresolution wavelet analysis Graphical Models Image Process. 59 5 1997 349-364
59. Heine J.J. Deans S.R. Cullers D.K. Stauduhar R. Clarke L.P. Multiresolution statistical analysis of high-resolution digital mammograms IEEE Trans. Med. Imag. 16 5 1997 503-515
60. H. Yoshida, W. Zhang, W. Cai, K. Doi, R.M. Nishikawa, M.L. Giger, Optimizing wavelet transform based on supervised learning for detection of microcalcifications in digital mammograms, Proceedings of the IEEE International Conference on Image Processing, Vol. 3, Washington, DC, October 1995, pp. 152-155.
61. R.N. Strickland, H.I. Hahn, Wavelet transforms for detecting microcalcifications in mammography, Proceedings of the International Conference on Image Processing, Austin, TX, 1994, pp. 402-406.
62. R.N. Strickland, H.I. Hahn, Wavelet transform matched filters for the detection and classification of microcalcifications in mammography, Proceedings of the 1995 IEEE International Conference on Image Processing, October 23-28, 1995, pp. 422-425.
63. R.N. Strickland, H.I. Hahn, L.J. Baig, Wavelet methods for combining CAD with enhancement of mammograms, Medical Imaging 1996: Image Processing, SPIE Proceedings, Vol. 2710, 1996, pp. 888-903.
64. Strickland R.N. Hahn H.I. Wavelet transform methods for object detection and recovery IEEE Trans. Image Process. 6 1997 724-735
65. W.J.H. Veldkamp, N. Karssemeijer, Normalization of local contrast in mammograms, IEEE Trans. Med. Imag. 19 (7) July, (2000) 731-738.
66. Lucier B.J. Kallergi M. Qian W. DeVore R.A. Clark R.A. Saff E.B. Clarke L.P. Wavelet compression and segmentation of digital mammograms J. Digital Imag. 7 1 1994 27-38
67. Zhang X.P. Desai M.D. Segmentation of bright targets using wavelets and adaptive thresholding IEEE Trans. Image Process. 10 7 2001 1020-1030
68. Clarke L.P. Kallergi M. Qian W. Li H.D. Clark R.A. Silbiger M.L. Tree-structured non-linear filter and wavelet transform for microcalcification segmentation in digital mammography Cancer Lett. 77 1994 173-181
69. Qian W. Kallergi M. Clarke L.P. Li H.D. Venugopal P. Tree structured wavelet transform segmentation of microcalcifications in digital mammography Med. Phys. 22 8 1995 1247-1253
70. R.N. Strickland, H. II Hahn, The wavelet transform as a multiresolution matched filter and zero-crossing detector for detecting microcalcifications in mammograms, Proceedings of the 1995 IEEE Engineering in Medicine and Biology 17th Annual Conference and 21st Canadian Medical and Biological Engineering Conference, September 20-23, 1995, pp. 1047-1048.
71. Donald L. McCandless A. Rogers S.K. Hoffmeigter M.J.W. Ruck M.D.W. Raines C.R.A. Suter B.W. Wavelet detection of clustered microcalcifications Proc. SPIE-Int. Soc. Opt. Eng. 2762 1996 388-399
72. D. Gunawan, Microcalcification detection using wavelet transform, IEEE Pacific RIM Conference on Communications, Computers and Signal Processing, August 26-28, 2001, pp. 694-697.
73. H.C. Choe, A.K. Chan, Microcalcification cluster detection in digitized mammograms using multiscale techniques, Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation, 1998, pp. 23-28.
74. W. Qian, L.P. Clarke, H.D. Li, R.A. Clark, M.L. Silbiger, Adaptive order statistic filtering and wavelet transform for feature enhancement in mammography, Proceedings of the Annual Conference on Engineering in Medicine and Biology, Vol. 15 (part 1), October 28-31, 1993, pp. 62-63.
75. Lado M.J. Tahoces P.G. Mendez A.J. Souto M. Vidal J.J. A wavelet-based algorithm for detecting clustered microcalcifications in digital mammograms Med. Phys. 26 7 1999 1294-1305
76. Qian W. Clarke L.P. Kallergi M. Clark R.A. Tree-structured nonlinear filters in digital mammography IEEE Trans. Med. Imag. 13 1 1994 25-36
77. Cheng T.W. Goldgof D.B. Hall L. Fast fuzzy clustering Fuzzy Sets and Systems 93 1998 49-56
78. Karssemeijer N. Adaptive noise equalization and recognition of microcalcification clusters in mammograms Int. J. Pattern Recognition Artif. Intell. 7 6 1993 1357-1376
79. Strickland R.N. Hahn H.II. Wavelet transforms for detecting microcalcifications in mammograms IEEE Trans. Med. Imag. 15 2 1996 218-229
80. Fam B.W. Olson S.L. Winter P.F. Scholz F.J. Algorithm for the detection of fine clustered calcifications on film mammograms Radiology 169 2 1988 333-337
81. W.J.H. Veldkamp, N. Karssemeijer, An improved method for detection of microcalcification clusters in digital mammograms, The SPIE Conference on Image Processing, Vol. 3661, February 1999, pp. 512-522.
82. N. Karssemeijer, A stochastic model for automated detection of calcifications in digital mammograms, 12th International Conference IPMI, Wye, UK, 1992, pp. 227-238.
83. Wallet B.C. Solka J.L. Priebe C.E. A method for detecting microcalcifications in digital mammograms J. Digital Imag. 10 3 1997 136-139
84. D. Song, W. Qian, L.P. Clarke, Digital mammography: hybrid M-channel wavelet transform for microcalcification segmentation, 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Amsterdam, 1996, pp. 1069-1070.
85. Dippel S. Stahl M. Wiemker R. Blaffert T. Multiscale contrast enhancement for radiographies: Laplacian pyramid versus fast wavelet transform IEEE Trans. Med. Imag. 21 4 2002 343-353
86. Netsch T. Peitgen H.O. Scale-space signatures for the detection of clustered microcalcifications in digital mammograms IEEE Trans. Med. Imag. 18 9 1999 774-786
87. T. Netsch, A scale-space approach for the detection of clustered microcalcifications in digital mammograms, Digital Mammography'96, Proceedings of the Third International Workshop Digital Mammography, Chicago, IL, June 1996, pp. 301-306.
88. Bothorel S. Meunier B.B. Muller S. A fuzzy logic based approach for semiological analysis of microcalcifications in mammographic images Int. J. Intelligent Systems 12 1997 819-848
89. H.D. Cheng, J.R. Chen, R.I. Freimanis, X.H. Jiang, A novel fuzzy logic approach to microcalcification detection, J. Inform. Sci. (1998) 1-14.
90. N. Pandey, Z. Salcic, J. Sivaswamy, Fuzzy logic based microcalcification detection, Neural Networks for Signal Processing-Proceedings of the IEEE Workshop, Vol. 2, December 11-13, 2000, pp. 662-671.
91. J.C. Olivo, Automatic detection of spots in biological images by a wavelet-based selective filtering technique, Proceedings of the 1996 IEEE International Conference on Image Processing, September 16-19, 1996, pp. 311-314.
92. Karssemeijer N. Recognition of microcalcification clusters in mammograms Int. J. Pattern Recognition Artif. Intell. 7 6 1993 1357-1376
93. Morrison S. Linnett L.M. A model based approach to object detection in digital mammography IEEE Int. Conf. Image Process. 2 1999 182-186
94. L. Zhang, W. Qian, R. Sankar, D. Song, R. Clark, A new false positive reduction method for MCCs detection in digital mammography, IEEE International Conference on Acoustics, Speech and Signal Processing, May 7-11, 2001, pp. 1033-1036.
95. Davies D.H. Dance D.R. Jones C.H. Automatic detection of clusters of calcifications in digital mammograms SPIE Med. Imag. IV: Image Process. 1233 1990 185-191
96. Chen C.H. Lee G.G. Image segmentation using multiresolution wavelet analysis and expectation-maximization (EM) algorithm for digital mammography J. Digital Imag. 8 1997 491-504
97. S. Sehad, S. Desarnaud, A. Strauss, Artificial neural classification of clustered microcalcifications on digitized mammograms, Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, Vol. 5, 1997, pp. 4217-4222.
98. K. Woods, C. Doss, K. Bowyer, L. Clarke, R. Clark, A neural network approach to microcalcification detection, IEEE 1992 Nuclear Science Symposium and Medical Imaging Conference, Orlando, FL (October 1992), 1992, pp. 1273-1275.
99. Bankman, J. Tsai, D. Kim, O. Gatewood, W. Brody, Detection of microcalcification clusters using neural networks, Annual International Conference of the IEEE Engineering in Medicine and Biology Society-Proceedings, Vol. 16, 1994, pp. 590-591.
100. DaPonte J.S. Sherman P. Classification of ultrasonic image texture by statistical discriminant analysis and neural networks Comput. Med. Imag. Graphics 15 1 1991 3-9
101. Yu S. Guan L. Brown S. Automatic detection of clustered microcalcification in digitized mammogram films J. Electron. Imag. 8 1 1999 76-82
102. R.M. Nishikawa, M.L. Giger, K. Dol, C.J. Vyborny, R.A. Schmidt, Computer-aided detection of clustered microcalcifications on digital mammograms, Med. Biol. Eng. Comput. 33 (2), March, (1995) 174-178.
103. S.A. Hojjatoleslami, J. Kittler, Detection of clusters of microcalcification using a K-nearest neighbour classifier, Proceedings of the 1996 IEE Colloquium on Digital Mammography, May 1996, pp. 1-6.
104. Spiesberger W. Mammogram inspection by computer IEEE Trans. Biol. Eng. BMF-26 4 1979 213-219
105. J. Marti, J. Batle, X. Cufi, J. Espanol, Microcalcification evaluation in computer assisted diagnosis for digital mammography, Proceedings of the 1999 EE Colloquium on Digital Mammography, 1999, pp. 1-6.
106. Nishikawa R.M. Jiang Y. Giger M.L. Vyborny C.J. Schmidt R.A. Bick R. Characterization of the mammographic appearance of microcalcifications: Applications in computer-aided diagnosis SPIE Image Process. 1898 1993 422-429
107. Marti J. Cufi X. Rgincos J. Espanol J. Pont J. Barcelo C. Shape-based features selection for microcalcification evaluation SPIE 3338 1998 1215-1224
108. T. Bhangale, U.B. Desai, U. Sharma, An unsupervised scheme for detection of microcalcifications on mammograms, IEEE International Conference on Image Processing, September 10-13, 2000, pp. 184-187.
109. C.Y. Enderwich, E.M. Tzanakou, Classification of mammographic tissue using shape and texture features, Proceedings of the 19th International Conference-IEEE/EMBS, 1997, pp. 810-813.
110. R.J. Ferrari, A.C.P.L.F. de Carvalho, P.M.A. Marques, A.F. Frere, Computerized classification of breast lesions:S shape and texture analysis using an artificial neural network, Image Process. Appl. (1999) 517-521.
111. Dhawan A.P. Chitre Y. Moskowitz M. Artificial neural network based classification of mammographic microcalcifications using image structure features Proc. SPIE 1905 1993 820-831
112. Meersman D. Scheunders P. Dyck D.V. Classification of microcalcifications using texture-based features Digital Mammography Nijmegen 1998 1998 233-236
113. Dhawan A.P. Chitre Y. Kaiser-Bonasso C. Moskowita M. Analysis of mammographic microcalcifications using grey-level image structure features IEEE Trans. Med. Imag. 15 3 1996 246-259
114. Lee C.S. Kim J.K. Park H.W. Computer-aided diagnostic system for breast cancer by detecting microcalcification SPIE 3335 1998 615-626
115. Geronimo J.S. Hardin D.P. Massopust P.R. Fractal functions and wavelet expansions based on several scaling functions J. Approx. Theory 78 1994 373-401
116. L. Gagnon, J.M. Lina, B. Goulard, Sharpening enhancement of digitized mammograms with complex symmetric Daubechies wavelets, Annual International Conference of the IEEE Engineering in Medicine and Biology-Proceedings, Vol. 17(1), 1995, pp. 543-544.
117. F. Rafiee-Rad, H. Soltanina-Zadeh, M. Rahmati, S. Pour-Abdollah, Microcalcification classification in mammograms using multiwavelet features, Proceedings of the 1999 Wavelet Applications in Signal and Image Processing, 1999, pp. 832-841.
118. Zadeh H.S. Nezhad S.P. Rad F.R. Texture feature extraction methods for microcalcification classification in mammograms Proc. SPIE 3979 2000 982-989
119. Rogova G.L. Stomper P.C. Ke C. Microcalcification texture analysis in a hybrid system for computer aided mammography SPIE 3661 1999 1426-1433
120. L.P. Cordella, F. Tortorella, M. Vento, Combing experts with different features for classifying clustered microcalcifications in mammograms, Proceedings of 15th International Conference on Patten Recognition, 2000, pp. 324-327.
121. Nishlkawa R.M. Giger M.L. Dio K. Vyborny C.J. Schmidt R.A. Computed-aided detection of clustered microcalcifications: An improved method for grouping detected signals Med. Phys. 20 6 1993 1661-1666
122. A.P. Dhawan, Y. Chitre, C. Bonasso, K. Wheeler, Radial-basis-function based classification of mammographic microcalcifications using texture features, IEEE Proceedings of the 1995 IEEE Engineering in Medicine and Biology 17th Annual Conference and 21st Canadian Medical and Biological Engineering Conference, September 20-23, 1995, 535-536.i
123. Chang T. Jay Kuo C.C. Texture analysis and classification with tree-structured wavelet transform IEEE Trans. Image. Proc. 2 4 1993 429-441
124. Laine A. Fan J. Texture classification by wavelet packet signatures IEEE Trans. Pattern Anal. Machine Intel. 15 11 1993 1186-1191
125. Caldwell C.B. Stapleton S.J. Holsworth D.W. Jong R.A. Characterization of mammographic parenchymal pattern by fractal dimension Phys. Med. Biol. 35 2 1990 235-247
126. Davies D.H. Dance D.R. Jones C.H. Automatic detection of microcalcifications in digital mammograms using local area thresholding techniques SPIE Med. Imag. III: Image Process. 1092 1989 153-157
127. Dani Kramer, Farzin Aghdasi, Texture analysis techniques for the classification of microcalcifications in digitized mammograms, Proceedings of the 1999 Fifth IEEE AFRICON Conference Electrotechnical Service for Africa, September 28-October 1, 1999, pp. 395-400.
128. Ema T. Doi K. Nishikawa R.M. Jiang Y. Papaioannou J. Image feature analysis and computer-aided diagnosis in mammography: Reduction of false-positive clustered microcalcifications using local edge-gradient analysis Med. Phys. 22 2 1995 161-169
129. D. Kramer, F. Aghdasi, Classification of microcalcifications in digitised mammograms using multiscale statistical texture analysis, Proceedings of the South African Symposium on Communications and Signal Processing, September 7-8, 1998, pp. 121-126.
130. C.M. Kocur, S.K. Gogers, L.R. Myers, T. Burns, M. Kabrisky, J.W. Hoffmeister, K.W. Baver, J.M. Steppe, Using neural networks to select wavelet features for breast cancer diagnosis, IEEE Eng. Med. Biol. 15 (3) May/June, (1996) 95-102.
131. A.P. Dhawan, Y. Chitre, M. Moskowitz, E. Gruenstein, Classification of mammographic microcalcification and structural features using an artificial neural network, Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Vol. 13(3), 1991, pp. 1105-1106.
132. Y. Chitre, A.P. Dhawan, M. Moskowitz, Artificial neural network based classification of mammographic microcalcifications using image structure and cluster features, Proceedings of the Annual Conference on Engineering in Medicine and Biology, Vol. 15, 1993, pp. 298-309.
133. Zadeh H.S. Nezhad S.P. Rad F.R. Shape-based and texture-based feature extraction for classification of microcalcification in mammograms Proc. SPIE 4322 2001 301-310
134. Y. Jiang, R.M. Nishikawa, D.E. Wolverton, C.E. Metz, R.A. Schmidt, K. Doi, Computerized classification of malignant and benign clustered microcalcifications in mammograms, Proceedings of 19th International Conference-IEEE/EMBS, October 30-November 2, 1997, pp. 521-523.
135. A.C. Patrocinio, H. Schiabel, R.H. Benatti, C.E. Goes, F.L.S. Nunes, Investigation of clustered microcalcification features for an automated classifier as part of a mammography CAD scheme, Proceedings of the 22nd Annual EMBS International Conference, July 23-28, 2000, pp. 1203-1205.
136. Gurcan M.N. Chan H.P. Sahiner B. Hadjiiski L. Petrick N. Helvie M.A. Optimal neural network architecture selection: improvement in computerized detection of microcalcifications Acad. Radiol. 9 4 2002 420-429
137. Guran M.N. Sahiner B. Chan H.P. Hadjiiski L. Petrick N. Selection of an optimal neural network architecture for computer-aided detection of microcalcifications-comparison of automated optimization techniques Med. Phys. 28 9 2001 1937-1948
138. Sahiner B. Chan H.P. Petrick N. Helvie M.A. Goodsitt M.M. Design of a high-sensitivity classifier based on a genetic algorithm: Application to computer-aided diagnosis Phys. Med. Biol. 43 1998 2853-2871
139. Anastasio M.A. Yoshida H. Nagel R. Nishikawa R.M. Doi K. A genetic algorithm-based method for optimizing the performance of a computer-aided diagnosis scheme for detection of clustered microcalcifications in mammograms Med. Phys. 25 9 1998 1613-1620
140. Chan H.P. Sahiner B. Lam K.L. Computerized analysis of mammographic microcalcifications in morphological and texture features space Med. Phys. 25 1998 2007-2019
141. B. Verma, A neural network based technique to locate and classify microcalcifications in digital mammograms, IEEE International Conference on Neural Networks-Conference Proceedings, Vol. 3, May 4-9, 1998, pp. 1790-1793.
142. B. Zheng, Y.H. Chang, X.H. Wang, W.F. Good, D. Gur, Application of a Bayesian belief network in a computer-assisted diagnosis scheme for mass detection, SPIE Conference on Image Processing, Vol. 3661, San Diego, CA, February 1999, pp. 1553-1560.
143. Li H.D. Kallergi M. Clarke L.P. Jain V.K. Clark R.A. Markov random field for tumor detection in digital mammography IEEE Trans. Med. Imag. 14 3 1995 565-576
144. Zheng L. Chan A.K. An artificial intelligent algorithm for tumor detection in screening mammogram IEEE Trans. Med. Imag. 20 17 2001 559-567
145. Jensen F.V. An Introduction to Bayesian Network 1996 Springer New York, NY
146. I.N. Bankman, W.A. Christens-Barry, D.W. Kim, I.N. Weinberg, O.B. Gatewood, W.R. Brody, Automated recognition of microcalcification clusters in mammograms, Proc. SPIE, 1905 (1993).
147. B. Zhang, Y.H. Chang, X.H. Wang, W.F. Good, Comparison of artificial neural network and Bayesian belief network in a computer-assisted diagnosis scheme for mammography, Proceedings of SPIE-The International Society for Optical Engineering, Vol. 3661, No. II, San Diego, CA, USA, February 22-25, 1999, pp. 1553-1561.
148. D.C. Edwards, J. Papaioannou, Y. Jiang, M.A. Kupinski, R.M. Nishikawa, Eliminating false-positive microcalcification clusters in a mammography CAD scheme using a Bayesian neural network, Proceedings of SPIE-The International Society for Optical Engineering, Vol. 4322(3), San Diego, CA, USA, February 19-22, 2001, pp. 1954-1960.
149. Kupinski M.A. Edwards D.C. Giger M.L. Metz C.E. Ideal observer approximation using Bayesian classification neural networks IEEE Trans. Med. Imag. 20 9 2001
150. Lyer N.S. Kandel A. Schneider M. Feature-based fuzzy classification for interpretation of mammograms Fuzzy Sets and Systems 114 2 2000 271-280
151. L.O. Hall, Learned fuzzy rules versus decision trees in classifying microcalcifications in mammograms, Proceedings of SPIE-The International Society for Optical Engineering, Vol. 2761, Orlando, FL, USA, April 1996, pp. 54-61.
152. Woods K. Sallam M.Y. Bowyer K.W. Evaluating detection algorithms Karssemeijer N. Thijssen M. Hendriks J. van Erning L. Digital Mammography Nijmegen 98 1998 19-45 Kluwer Academic Publisher Amsterdam
153. Metz C.E. ROC methodology in radiologic imaging Invest. Radiol. 21 9 1986 720-733
154. Swets J.A. ROC analysis applied to the evaluation of medical imaging techniques Invest. Radiol. 14 2 1979 109-121
155. Maria J.L. Pablo G.T. Miguel S. Arturo J.M. Juan J.V. Real and simulated clustered microcalcifications in digital mammograms: ROC study of observer performance Med. Phys. 24 9 1997 1385-1394
156. Jean H. David M.C. Charles F.B. Zygmunt P. Edward J.D. Preclinical ROC studies of digital stereomammography IEEE Trans. Med. Imag. 14 2 1995 318-327
157. Woods K. Kevin W.B. Generating ROC curves for artificial neural networks IEEE Trans. Med. Imag. 16 3 1997 329-331
158. K. Woods, K. Bowyer, A general view of detection algorithms, Proceedings of the Third International Workshop on Digital Mammography, Chicago, 1996, pp. 385-390.
159. Wald A. Statistical Decision Functions 1950 Wiley New York
160. Lusted L.B. Introduction to Medical Decision Making 1968 Thomas Springfield, IL
161. Lusted L.B. Decision-making studies in patient management N. Engl. J. Med. 284 1971 416-424
162. Lusted L.B. Signal detectability and medical decision-making Science 171 1971 1217-1219
163. C.E. Metz, P.L. Wang, H.B. Kronman, A new approach for testing the significance of differences between ROC curves measured from correlated data, Proceedings of the Info. Proc. Med. Imaging Eighth Conference, Boston, MA, 1984, pp. 432-445.
164. Egan J.P. Greenberg G.Z. Schulman A.I. Operating characteristics, signal detectability, and the method of free response J. Acoust. Soc. Am. 33 1961 993-1007
165. Bunch P.C. Hamilton J.F. Sanderson G.K. Simmons A.H. A free-response approach to the measurement and characterization of radiographic observer performance J. Appl. Photogr. Eng. 4 1978 166-171
166. Chakraborty D.P. Free-response methodology: alternate analysis and a new observer performance experiment Radiology 174 1990 873-881
167. Dorfman D.D. Alf E.Jr. Maximum-likelihood estimation of parameters of signal detection theory and determination of confidence intervals: rating method data J. Math. Psychol. 6 1969 487-496
168. Roehrig J. Doi T. Hasegawa A. Hunt B. Marshall J. Romsdahl H. Schneider A. Sharbaugh R. Zhang W. Clinical results with R2 Image Checker system Karssemeijer N. Thijssen M. Hendriks J. van Erning L. Digital Mammography Nijmegen 98 1998 395-400 Kluwer Academic Publisher Amsterdam
169. http://www.r2tech.com. R2 Technology Company
170. Nishikawa R.M. Giger M.L. Wolverton D.E. Schimidt R.A. Comstock C.E. Papaioannou J. Collins S.A. Doi K. Prospective testing of a clinical mammography workstation for CAD: Analysis of the first 10,000 cases Karssemeijer N. Thijssen M. Hendriks J. van Erning L. Digital Mammography Nijmegen 98 1998 401-406 Kluwer Academic Publisher Amsterdam
171. A. Krupinski Elizabeth Clinical applications-present and future Karssemeijer N. Thijssen M. Hendriks J. van Erning L. Digital Mammography Nijmegen 98 1998 47-70 Kluwer Academic Publisher Amsterdam
172. Karssemeijer N. Frieling J.T.M. Hendricks J.H.C.L. Spatial resolution in digital mammography Invest Radiol. 24 1989 234
173. Fatemi M. Wold L.E. Alizad A. Greenleaf J.F. Vibro-acoustic tissue mammography IEEE Trans. Med. Imag. 21 1 2002 1-8
174. R.J. Grable, S.L. Ponder, N.A. Gkanatsios, W. Dieckmann, P. Oliver, R.H. Wake, Y. Zeng, Optical computed tomography for imaging the breast: first look, Proceedings of SPIE-the International Society for Optical Engineering, Vol. 4082, July 26-28, 2000, pp. 40-45.
175. Zonderland H.M. Diagnosis of breast cancer: Contribution of US as an adjunct to mammography Radiology 213 2 1999 413-422
176. Kasumi F. Can microcalcification located within breast carcinomas be detected by ultrasound imaging Ultrasound Med. Biol. 14 1 1988 175-182
177. Yang W.T. Suen M. Ahuja A. Meterweli C. In vivo demonstration of microcalcification in breast cancer using high resolution ultrasound Br. J. Radiol. 70 1997 685-690
178. Fatemi M. Greenleaf J.F. Vibro-acoustography system modeling Era of Hope Proc. 1 2000 192
179. McCauley T.G. Stewart A. Stanton M. Wu T. Phillips W. Three-dimension breast image reconstruction from a limited number of views Proc. SPIE-Int. Soc. Opt. Eng. 3977 2000 384-395
180. Jayaram K. Udupa, Gabor T. Herman, 3D Imaging in Medicine, Vols. I and II, CRC Press, Boca Raton, FL, 1991, 1999.
181. K. Udupa Jayaram T. Herman Gabor Medical image reconstruction, processing, visualization, and analysis: The MIPG perspective IEEE Trans. Med. Imag. 21 4 2002 281-295
182. Samani A. Bishop J. Yaffe M.J. Plewes D.B. Biomechanical 3-D finite element modeling of the human breast using MRI data IEEE Trans. Med. Imag. 20 4 2001 271-279
183. S.P. Bates, S.M. Astley, J.D. Davies, S. Sharp, Three-dimensional reconstruction and shape classification of microcalcification clusters in breast lesions, Proceedings of the Third International Workshop Digital Mammography, Chicago, IL, 1996, pp. 239-244.
184. A.D.A. Maidment, 3-dimension analysis of breast calcifications, Proceedings of the Third International Workshop Digital Mammography, Chicago, IL, 1996, pp. 245-250.
185. Yam M. Brady M. Highnam R. Behrehbuch C. English R. Kita Y. Three-dimensional reconstruction of microcalcification clusters from two mammographic view IEEE Trans. Med. Imag. 20 6 2001 479-489
186. Tang H. Zhuang T. X. Wu Ed Realizations of fast 2-D/3-D image filtering and enhancement IEEE Trans. Med. Imag. 20 2 2001 132-140