CADx of mammographic masses and clustered microcalcifications: A review

Medical Physics

Volumn 36, Issue 6, 2009, Pages 2052-2068

  Elter, Matthias ^a   Horsch, Alexander ^b,c  

^a FRAUNHOFER INSTITUTE FOR INTEGRATED CIRCUITS IIS   (Germany)

^b TECHNICAL UNIVERSITY OF MUNICH   (Germany)

^c UNIVERSITY OF TROMSØ   (Norway)

Author keywords

CADx; Computer aided diagnosis; Mammography; Review

Indexed keywords

CALCIFICATION (BIOCHEMISTRY); DISEASES; MAMMOGRAPHY; REVIEWS; SURVEYS; X RAY SCREENS;

CADX; CLUSTERED MICROCALCIFICATIONS; COMPUTER AIDED DETECTION; COMPUTERAIDED DIAGNOSES (CADX); DETECTION AND DIAGNOSIS; ERROR PRONE TASKS; INTERNATIONAL JOURNALS; MAMMOGRAPHIC MASS;

COMPUTER AIDED DIAGNOSIS;

ARTICLE; AUTOANALYSIS; BREAST CALCIFICATION; BREAST TUMOR; CANCER DIAGNOSIS; COMPUTER ASSISTED RADIOGRAPHY; COMPUTER PROGRAM; DIAGNOSTIC PROCEDURE; EXTRACTION; HUMAN; IMAGE ANALYSIS; MAMMOGRAPHY; MORPHOLOGY; OPTICAL DENSITY; PRIORITY JOURNAL;

EID: 66449127098     PISSN: 00942405     EISSN: None     Source Type: Journal    
DOI: 10.1118/1.3121511     Document Type: Article

References (146)

1. American Cancer Society, Breast Cancer Facts & Figures 2007-2008 (American Cancer Society, Atlanta, 2007).
2. R. M. Nishikawa, " Current status and future directions of computer-aided diagnosis in mammography.," Comput. Med. Imaging Graph. 31 (4-5), 224-235 (2007). 10.1016/j.compmedimag.2007.02.009
3. G. Hermann, C. Janus, I. S. Schwartz, B. Krivisky, S. Bier, and J. G. Rabinowitz, " Nonpalpable breast lesions: Accuracy of prebiopsy mammographic diagnosis.," Radiology 165 (2), 323-326 (1987). (Pubitemid 17160671)
4. D. B. Kopans, " The positive predictive value of mammography.," AJR, Am. J. Roentgenol. 158 (3), 521-526 (1992).
5. D. D. Adler and M. A. Helvie, " Mammographic biopsy recommendations.," Curr. Opin. Radiol. 4 (5), 123-129 (1992).
6. J. G. Elmore, C. Y. Nakano, T. D. Koepsell, L. M. Desnick, C. J. D'Orsi, and D. F. Ransohoff, " International variation in screening mammography interpretations in community-based programs.," J. Natl. Cancer Inst. 95 (18), 1384-1393 (2003). (Pubitemid 37220458)
7. W. E. Barlow, C. Chi, P. A. Carney, S. H. Taplin, C. D'Orsi, G. Cutter, R. E. Hendrick, and J. G. Elmore, " Accuracy of screening mammography interpretation by characteristics of radiologists.," J. Natl. Cancer Inst. 96 (24), 1840-1850 (2004). (Pubitemid 40081321)
8. R. E. Bird, T. W. Wallace, and B. C. Yankaskas, " Analysis of cancers missed at screening mammography.," Radiology 184 (3), 613-617 (1992).
9. L. Shen, R. M. Rangayyan, and J. L. Desautels, " Application of shape analysis to mammographic calcifications.," IEEE Trans. Med. Imaging 13 (2), 263-274 (1994). 10.1109/42.293919
10. Y. Jiang, R. M. Nishikawa, D. E. Wolverton, C. E. Metz, M. L. Giger, R. A. Schmidt, C. J. Vyborny, and K. Doi, " Malignant and benign clustered microcalcifications: Automated feature analysis and classification.," Radiology 198 (3), 671-678 (1996). (Pubitemid 26066280)
11. S. Paquerault, L. M. Yarusso, J. Papaioannou, Y. Jiang, and R. M. Nishikawa, " Radial gradient-based segmentation of mammographic microcalcifications: Observer evaluation and effect on cad performance.," Med. Phys. 31 (9), 2648-2657 (2004). 10.1118/1.1767692
12. A. P. Dhawan, Y. Chitre, and C. Kaiser-Bonasso, " Analysis of mammographic microcalcifications using gray-level image structure features.," IEEE Trans. Med. Imaging 15 (3), 246-259 (1996). 10.1109/42.500063 (Pubitemid 126780316)
13. I. Leichter, R. Lederman, P. Bamberger, B. Novak, S. Fields, and S. S. Buchbinder, " The use of an interactive software program for quantitative characterization of microcalcifications on digitized film-screen mammograms.," Invest. Radiol. 34 (6), 394-400 (1999). 10.1097/00004424- 199906000-00002
14. F. Schmidt, E. Sorantin, C. Szepesv̀ri, E. Graif, M. Becker, H. Mayer, and K. Hartwagner, " An automatic method for the identification and interpretation of clustered microcalcifications in mammograms.," Phys. Med. Biol. 44 (5), 1231-1243 (1999). 10.1088/0031-9155/44/5/011
15. L. P. Clarke, M. Kallergi, W. Qian, H. D. Li, R. A. Clark, and M. L. Silbiger, " Tree-structured non-linear filter and wavelet transform for microcalcification segmentation in digital mammography.," Cancer Lett. 77 (2-3), 173-181 (1994). 10.1016/0304-3835(94)90100-7
16. W. Qian, M. Kallergi, L. P. Clarke, H. D. Li, P. Venugopal, D. Song, and R. A. Clark, " Tree structured wavelet transform segmentation of microcalcifications in digital mammography.," Med. Phys. 22 (8), 1247-1254 (1995). 10.1118/1.597562
17. R. N. Strickland and H. I. Hahn, " Wavelet tranforms for detecting microcalcifications in mammograms.," IEEE Trans. Med. Imaging 15 (2), 218-229 (1996). 10.1109/42.491423 (Pubitemid 126780314)
18. H. Yoshida, K. Doi, R. M. Nishikawa, M. L. Giger, and R. A. Schmidt, " An improved computer-assisted diagnostic scheme using wavelet transform for detecting clustered microcalcifications in digital mammograms.," Acad. Radiol. 3 (8), 621-627 (1996). 10.1016/S1076-6332(96)80186-3
19. J. J. Heine, S. R. Deans, D. K. Cullers, R. Stauduhar, and L. P. Clarke, " Multiresolution statistical analysis of high-resolution digital mammograms.," IEEE Trans. Med. Imaging 16 (5), 503-515 (1997). 10.1109/42.640740 (Pubitemid 127767629)
20. W. Zhang, H. Yoshida, R. M. Nishikawa, and K. Doi, " Optimally weighted wavelet transform based on supervised training for detection of microcalcifications in digital mammograms.," Med. Phys. 25 (6), 949-956 (1998). 10.1118/1.598273
21. W. Qian, L. P. Clarke, D. Song, and R. A. Clark, " Digital mammography: Hybrid four-channel wavelet transform for microcalcification segmentation.," Acad. Radiol. 5 (5), 354-364 (1998). 10.1016/S1076-6332(98) 80154-2
22. T. C. Wang and N. B. Karayiannis, " Detection of microcalcifications in digital mammograms using wavelets.," IEEE Trans. Med. Imaging 17 (4), 498-509 (1998). 10.1109/42.730395 (Pubitemid 128747706)
23. M. J. Lado, P. G. Tahoces, A. J. Ḿndez, M. Souto, and J. J. Vidal, " A wavelet-based algorithm for detecting clustered microcalcifications in digital mammograms.," Med. Phys. 26 (7), 1294-1305 (1999). 10.1118/1.598624
24. S. Yu and L. Guan, " A CAD system for the automatic detection of clustered microcalcifications in digitized mammogram films.," IEEE Trans. Med. Imaging 19 (2), 115-126 (2000). 10.1109/42.896785
25. P. Heinlein, J. Drexl, and W. Schneider, " Integrated wavelets for enhancement of microcalcifications in digital mammography.," IEEE Trans. Med. Imaging 22 (3), 402-413 (2003). 10.1109/TMI.2003.809632
26. G. Lemaur, K. Drouiche, and J. DeConinck, " Highly regular wavelets for the detection of clustered microcalcifications in mammograms.," IEEE Trans. Med. Imaging 22 (3), 393-401 (2003). 10.1109/TMI.2003.809580
27. E. Regentova, L. Zhang, J. Zheng, and G. Veni, " Microcalcification detection based on wavelet domain hidden markov tree model: study for inclusion to computer aided diagnostic prompting system.," Med. Phys. 34 (6), 2206-2219 (2007). 10.1118/1.2733800
28. T. Netsch and H. O. Peitgen, " Scale-space signatures for the detection of clustered microcalculations in digital mammograms.," IEEE Trans. Med. Imaging 18 (9), 774-786 (1999). 10.1109/42.802755
29. M. F. Salfity, R. M. Nishikawa, Y. Jiang, and J. Papaioannou, " The use of a priori information in the detection of mammographic microcalcifications to improve their classification.," Med. Phys. 30 (5), 823-831 (2003). 10.1118/1.1559884
30. R. M. Nishikawa, M. L. Giger, K. Doi, C. J. Vyborny, and R. A. Schmidt, " Computer-aided detection of clustered microcalcifications on digital mammograms.," Med. Biol. Eng. Comput. 33 (2), 174-178 (1995). 10.1007/BF02523037
31. D. Betal, N. Roberts, and G. H. Whitehouse, " Segmentation and numerical analysis of microcalcifications on mammograms using mathematical morphology.," Br. J. Radiol. 70 (837), 903-917 (1997). (Pubitemid 27401719)
32. J. C. Fu, S. K. Lee, S. T. C. Wong, J. Y. Yeh, A. H. Wang, and H. K. Wu, " Image segmentation feature selection and pattern classification for mammographic microcalcifications.," Comput. Med. Imaging Graph. 29 (6), 419-429 (2005). 10.1016/j.compmedimag.2005.03.002
33. J. Dengler, S. Behrens, and J. F. Desaga, " Segmentation of microcalcifications in mammograms.," IEEE Trans. Med. Imaging 12 (4), 634-642 (1993). 10.1109/42.251111
34. N. Ibrahim, H. Fujita, T. Hara, and T. Endo, " Automated detection of clustered microcalcifications on mammograms: Cad system application to mias database.," Phys. Med. Biol. 42 (12), 2577-2589 (1997). 10.1088/0031-9155/42/12/021
35. M. G. Linguraru, K. Marias, R. English, and M. Brady, " A biologically inspired algorithm for microcalcification cluster detection.," Med. Image Anal. 10 (6), 850-862 (2006). 10.1016/j.media.2006.07.004
36. R. Nakayama, Y. Uchiyama, R. Watanabe, S. Katsuragawa, K. Namba, and K. Doi, " Computer-aided diagnosis scheme for histological classification of clustered microcalcifications on magnification mammograms.," Med. Phys. 31 (4), 789-799 (2004). 10.1118/1.1655711
37. R. Nakayama, R. Watanabe, K. Namba, K. Takeda, K. Yamamoto, S. Katsuragawa, and K. Doi, " Computer-aided diagnosis scheme for identifying histological classification of clustered microcalcifications by use of follow-up magnification mammograms.," Acad. Radiol. 13 (10), 1219-1228 (2006). 10.1016/j.acra.2006.07.005
38. F. Lefebvre, H. Benali, R. Gilles, E. Kahn, and R. Di Paola, " A fractal approach to the segmentation of microcalcifications in digital mammograms.," Med. Phys. 22 (4), 381-390 (1995). 10.1118/1.597473
39. H. Li, K. J. Liu, and S. C. Lo, " Fractal modeling and segmentation for the enhancement of microcalcifications in digital mammograms.," IEEE Trans. Med. Imaging 16 (6), 785-798 (1997). 10.1109/42.650875 (Pubitemid 127770438)
40. L. Bocchi, G. Coppini, J. Nori, and G. Valli, " Detection of single and clustered microcalcifications in mammograms using fractals models and neural networks.," Med. Eng. Phys. 26 (4), 303-312 (2004). 10.1016/j.medengphy. 2003.11.009
41. H. D. Cheng, Y. M. Lui, and R. I. Freimanis, " A novel approach to microcalcification detection using fuzzy logic technique.," IEEE Trans. Med. Imaging 17 (3), 442-450 (1998). 10.1109/42.712133 (Pubitemid 128747698)
42. B. Verma and J. Zakos, " A computer-aided diagnosis system for digital mammograms based on fuzzy-neural and feature extraction techniques.," IEEE Trans. Inf. Technol. Biomed. 5 (1), 46-54 (2001). 10.1109/4233.908389
43. N. Karssemeijer, " Adaptive noise equalization and recognition of microcalcification clusters in mammograms.," Int. J. Pattern Recognit. Artif. Intell. 7 (6), 1357-1376 (1993). 10.1142/S0218001493000662
44. W. J. Veldkamp and N. Karssemeijer, " Normalization of local contrast in mammograms.," IEEE Trans. Med. Imaging 19 (7), 731-738 (2000). 10.1109/42.875197
45. K. J. McLoughlin, P. J. Bones, and N. Karssemeijer, " Noise equalization for detection of microcalcification clusters in direct digital mammogram images.," IEEE Trans. Med. Imaging 23 (3), 313-320 (2004). 10.1109/TMI.2004.824240
46. R. M. Rangayyan, N. M. El-Faramawy, J. E. Desautels, and O. A. Alim, " Measures of acutance and shape for classification of breast tumors.," IEEE Trans. Med. Imaging 16 (6), 799-810 (1997). 10.1109/42.650876 (Pubitemid 127770439)
47. L. M. Bruce and R. R. Adhami, " Classifying mammographic mass shapes using the wavelet transform modulus-maxima method.," IEEE Trans. Med. Imaging 18 (12), 1170-1177 (1999). 10.1109/42.819326
48. J. Kilday, J. Kilday, F. Palmieri, and M. D. Fox, " Classifying mammographic lesions using computerized image analysis.," IEEE Trans. Med. Imaging 12 (4), 664-669 (1993). 10.1109/42.251116
49. M. L. Giger, C. J. Vyborny, and R. A. Schmidt, " Computerized characterization of mammographic masses: Analysis of spiculation.," Cancer Lett. 77 (2-3), 201-211 (1994). 10.1016/0304-3835(94)90103-1
50. Z. Huo, M. L. Giger, C. J. Vyborny, U. Bick, P. Lu, D. E. Wolverton, and R. A. Schmidt, " Analysis of spiculation in the computerized classification of mammographic masses.," Med. Phys. 22 (10), 1569-1579 (1995). 10.1118/1.597626
51. M. A. Kupinski and M. L. Giger, " Automated seeded lesion segmentation on digital mammograms.," IEEE Trans. Med. Imaging 17 (4), 510-517 (1998). 10.1109/42.730396 (Pubitemid 128747707)
52. N. Petrick, H. P. Chan, B. Sahiner, and M. A. Helvie, " Combined adaptive enhancement and region-growing segmentation of breast masses on digitized mammograms.," Med. Phys. 26 (8), 1642-1654 (1999). 10.1118/1.598658
53. B. Sahiner, H. P. Chan, N. Petrick, M. A. Helvie, and M. M. Goodsitt, " Computerized characterization of masses on mammograms: The rubber band straightening transform and texture analysis.," Med. Phys. 25 (4), 516-526 (1998). 10.1118/1.598228
54. A. J. Ḿndez, P. G. Tahoces, M. J. Lado, M. Souto, and J. J. Vidal, " Computer-aided diagnosis: Automatic detection of malignant masses in digitized mammograms.," Med. Phys. 25 (6), 957-964 (1998). 10.1118/1.598274
55. S. Pohlman, K. A. Powell, N. A. Obuchowski, W. A. Chilcote, and S. Grundfest-Broniatowski, " Quantitative classification of breast tumors in digitized mammograms.," Med. Phys. 23 (8), 1337-1345 (1996). 10.1118/1.597707
56. D. Guliato, R. M. Rangayyan, W. A. Carnielli, J. A. Zuffo, and J. E. Leo Desautels, " Segmentation of breast tumors in mammograms using fuzzy sets.," J. Electron. Imaging 12, 369-378 (2003). 10.1117/1.1579017
57. G. M. te Brake and N. Karssemeijer, " Segmentation of suspicious densities in digital mammograms.," Med. Phys. 28 (2), 259-266 (2001). 10.1118/1.1339884
58. B. Sahiner, N. Petrick, H. P. Chan, L. M. Hadjiiski, C. Paramagul, M. A. Helvie, and M. N. Gurcan, " Computer-aided characterization of mammographic masses: Accuracy of mass segmentation and its effects on characterization., " IEEE Trans. Med. Imaging 20 (12), 1275-1284 (2001). 10.1109/42.974922
59. B. Sahiner, H. P. Chan, N. Petrick, M. A. Helvie, and L. M. Hadjiiski, " Improvement of mammographic mass characterization using spiculation measures and morphological features.," Med. Phys. 28 (7), 1455-1465 (2001). 10.1118/1.1381548
60. J. Shi, B. Sahiner, H.-P. Chan, J. Ge, L. Hadjiiski, M. A. Helvie, A. Nees, Y.-T. Wu, J. Wei, C. Zhou, Y. Zhang, and J. Cui, " Characterization of mammographic masses based on level set segmentation with new image features and patient information.," Med. Phys. 35 (1), 280-290 (2008). 10.1118/1.2820630
61. Y. Yuan, M. L. Giger, H. Li, K. Suzuki, and C. Sennett, " A dual-stage method for lesion segmentation on digital mammograms.," Med. Phys. 34 (11), 4180-4193 (2007). 10.1118/1.2790837
62. S. Timp and N. Karssemeijer, " A new 2d segmentation method based on dynamic programming applied to computer aided detection in mammography.," Med. Phys. 31 (5), 958-971 (2004). 10.1118/1.1688039
63. C. Varela, S. Timp, and N. Karssemeijer, " Use of border information in the classification of mammographic masses.," Phys. Med. Biol. 51 (2), 425-441 (2006). 10.1088/0031-9155/51/2/016
64. A. Rojas Domínguez and A. K. Nandi, " Improved dynamic-programming-based algorithms for segmentation of masses in mammograms.," Med. Phys. 34 (11), 4256-4269 (2007). 10.1118/1.2791034
65. A. Papadopoulos, D. I. Fotiadis, and A. Likas, " Characterization of clustered microcalcifications in digitized mammograms using neural networks and support vector machines.," Artif. Intell. Med. 34 (2), 141-150 (2005). 10.1016/j.artmed.2004.10.001
66. M. Kallergi, " Computer-aided diagnosis of mammographic microcalcification clusters.," Med. Phys. 31 (2), 314-326 (2004). 10.1118/1.1637972
67. W. J. Veldkamp, N. Karssemeijer, J. D. Otten, and J. H. Hendriks, " Automated classification of clustered microcalcifications into malignant and benign types.," Med. Phys. 27 (11), 2600-2608 (2000). 10.1118/1.1318221
68. L. Wei, Y. Yang, R. M. Nishikawa, and Y. Jiang, " A study on several machine-learning methods for classification of malignant and benign clustered microcalcifications.," IEEE Trans. Med. Imaging 24 (3), 371-380 (2005). 10.1109/TMI.2004.842457
69. American College of Radiology, Breast Imaging Reporting and Data System BI-RADS Atlas, 2006.
70. H. Soltanian-Zadeh, F. Rafiee-Rad, and S. Pourabdollah-Nejad, " Comparison of multiwavelet, wavelet, haralick and shape features for microcalcification classification in mammograms.," Pattern Recogn. 37, 1973-1986 (2004). 10.1016/j.patcog.2003.03.001
71. L. Bocchi and J. Nori, " Shape analysis of microcalcifications using radon transform.," Med. Eng. Phys. 29 (6), 691-698 (2007). 10.1016/j.medengphy.2006.07.012
72. R. M. Haralick, K. Shanmugam, and I. Dinstein, " Textural features for image classification.," IEEE Trans. Syst. Man Cybern. 3 (6), 610-621 (1973). 10.1109/TSMC.1973.4309314
73. D. L. Thiele, C. Kimme-Smith, T. D. Johnson, M. McCombs, and L. W. Bassett, " Using tissue texture surrounding calcification clusters to predict benign vs malignant outcomes.," Med. Phys. 23 (4), 549-555 (1996). 10.1118/1.597901
74. H. P. Chan, B. Sahiner, N. Petrick, M. A. Helvie, K. L. Lam, D. D. Adler, and M. M. Goodsitt, " Computerized classification of malignant and benign microcalcifications on mammograms: Texture analysis using an artificial neural network.," Phys. Med. Biol. 42 (3), 549-567 (1997). 10.1088/0031-9155/42/3/ 008
75. H. P. Chan, B. Sahiner, K. L. Lam, N. Petrick, M. A. Helvie, M. M. Goodsitt, and D. D. Adler, " Computerized analysis of mammographic microcalcifications in morphological and texture feature spaces.," Med. Phys. 25 (10), 2007-2019 (1998). 10.1118/1.598389
76. A. Laine and J. Fan, " Texture classification by wavelet packet signatures.," IEEE Trans. Pattern Anal. Mach. Intell. 15 (11), 1186-1191 (1993). 10.1109/34.244679
77. L. Tabar, P. B. Dean, and T. Tot, Teaching Atlas of Mammography, 3rd ed. (Thieme, New York, 2001).
78. D. M. Catarious, A. H. Baydush, and C. E. Floyd, " Incorporation of an iterative, linear segmentation routine into a mammographic mass cad system.," Med. Phys. 31 (6), 1512-1520 (2004). 10.1118/1.1738960
79. B. Zheng, A. Lu, L. A. Hardesty, J. H. Sumkin, C. M. Hakim, M. A. Ganott, and D. Gur, " A method to improve visual similarity of breast masses for an interactive computer-aided diagnosis environment.," Med. Phys. 33 (1), 111-117 (2006). 10.1118/1.2143139
80. Z. Huo, M. L. Giger, C. J. Vyborny, D. E. Wolverton, R. A. Schmidt, and K. Doi, " Automated computerized classification of malignant and benign masses on digitized mammograms.," Acad. Radiol. 5 (3), 155-168 (1998). 10.1016/S1076-6332(98)80278-X
81. Z. Huo, M. L. Giger, C. J. Vyborny, D. E. Wolverton, and C. E. Metz, " Computerized classification of benign and malignant masses on digitized mammograms: A study of robustness.," Acad. Radiol. 7 (12), 1077-1084 (2000). 10.1016/S1076-6332(00)80060-4
82. B. Sahiner, H. P. Chan, N. Petrick, M. A. Helvie, and M. M. Goodsitt, " Design of a high-sensitivity classifier based on a genetic algorithm: Application to computer-aided diagnosis.," Phys. Med. Biol. 43 (10), 2853-2871 (1998). 10.1088/0031-9155/43/10/014
83. L. Hadjiiski, B. Sahiner, H. P. Chan, N. Petrick, and M. Helvie, " Classification of malignant and benign masses based on hybrid art2lda approach.," IEEE Trans. Med. Imaging 18 (12), 1178-1187 (1999). 10.1109/42.819327
84. N. R. Mudigonda, R. M. Rangayyan, and J. E. Desautels, " Gradient and texture analysis for the classification of mammographic masses.," IEEE Trans. Med. Imaging 19 (10), 1032-1043 (2000). 10.1109/42.887618
85. G. M. te Brake, N. Karssemeijer, and J. H. Hendriks, " An automatic method to discriminate malignant masses from normal tissue in digital mammograms.," Phys. Med. Biol. 45 (10), 2843-2857 (2000). 10.1088/0031-9155/45/10/308
86. W. K. Lim and M. J. Er, " Classification of mammographic masses using generalized dynamic fuzzy neural networks.," Med. Phys. 31 (5), 1288-1295 (2004). 10.1118/1.1708643
87. S. Gupta and M. K. Markey, " Correspondence in texture features between two mammographic views.," Med. Phys. 32 (6), 1598-1606 (2005). 10.1118/1.1915013
88. M. E. Mavroforakis, H. V. Georgiou, N. Dimitropoulos, D. Cavouras, and S. Theodoridis, " Mammographic masses characterization based on localized texture and dataset fractal analysis using linear, neural and support vector machine classifiers.," Artif. Intell. Med. 37 (2), 145-162 (2006). 10.1016/j.artmed.2006.03.002
89. M. Heath, K. Bowyer, D. Kopans, R. Moore, and W. P. Kegelmeyer, in Proceedings of the Fifth International Workshop on Digital Mammography, edited by, M. J. Yaffe, (Medical Physics Publishing, 2001), pp. 212-218.
90. R. O. Duda, P. E. Hart, and D. G. Stork, Pattern Classification (Wiley-Interscience, New York, 2000).
91. R. Nakayama, R. Watanabe, K. Namba, K. Takeda, K. Yamamoto, S. Katsuragawa, and K. Doi, " An improved computer-aided diagnosis scheme using the nearest neighbor criterion for determining histological classification of clustered microcalcifications.," Methods Inf. Med. 46 (6), 716-722 (2007). (Pubitemid 350305431)
92. Y. Wu, M. L. Giger, K. Doi, C. J. Vyborny, R. A. Schmidt, and C. E. Metz, " Artificial neural networks in mammography: Application to decision making in the diagnosis of breast cancer.," Radiology 187 (1), 81-87 (1993). (Pubitemid 23097863)
93. J. Y. Lo, J. A. Baker, P. J. Kornguth, J. D. Iglehart, and C. E. Floyd, " Predicting breast cancer invasion with artificial neural networks on the basis of mammographic features.," Radiology 203 (1), 159-163 (1997). (Pubitemid 27142724)
94. C. Markopoulos, E. Kouskos, K. Koufopoulos, V. Kyriakou, and J. Gogas, " Use of artificial neural networks (computer analysis) in the diagnosis of microcalcifications on mammography.," Eur. J. Radiol. 39 (1), 60-65 (2001). 10.1016/S0720-048X(00)00281-3
95. J. L. Jesneck, J. Y. Lo, and J. A. Baker, " Breast mass lesions: Computer-aided diagnosis models with mammographic and sonographic descriptors.," Radiology 244 (2), 390-398 (2007). 10.1148/radiol.2442060712
96. S. Gupta, P. F. Chyn, and M. K. Markey, " Breast cancer cadx based on bi-rads descriptors from two mammographic views.," Med. Phys. 33 (6), 1810-1817 (2006). 10.1118/1.2188080
97. A. A. J. Roelofs, N. Karssemeijer, N. Wedekind, C. Beck, S. van Woudenberg, P. R. Snoeren, J. H. C. L. Hendriks, M. Rosselli del Turco, N. Bjurstam, H. Junkermann, D. Beijerinck, B. Śradour, and C. J. G. Evertsz, " Importance of comparison of current and prior mammograms in breast cancer screening.," Radiology 242 (1), 70-77 (2007). 10.1148/radiol. 2421050684
98. C. Varela, N. Karssemeijer, J. H. C. L. Hendriks, and R. Holland, " Use of prior mammograms in the classification of benign and malignant masses.," Eur. J. Radiol. 56 (2), 248-255 (2005). 10.1016/j.ejrad.2005.04. 007
99. S. Timp and N. Karssemeijer, " Interval change analysis to improve computer aided detection in mammography.," Med. Image Anal. 10 (1), 82-95 (2006). 10.1016/j.media.2005.03.007
100. L. Hadjiiski, B. Sahiner, H. P. Chan, N. Petrick, M. A. Helvie, and M. Gurcan, " Analysis of temporal changes of mammographic features: Computer-aided classification of malignant and benign breast masses.," Med. Phys. 28 (11), 2309-2317 (2001). 10.1118/1.1412242
101. S. Timp, C. Varela, and N. Karssemeijer, " Temporal change analysis for characterization of mass lesions in mammography.," IEEE Trans. Med. Imaging 26 (7), 945-953 (2007). 10.1109/TMI.2007.897392
102. S. Sanjay-Gopal, H. P. Chan, T. Wilson, M. Helvie, N. Petrick, and B. Sahiner, " A regional registration technique for automated interval change analysis of breast lesions on mammograms.," Med. Phys. 26 (12), 2669-2679 (1999). 10.1118/1.598806
103. P. Filev, L. Hadjiiski, B. Sahiner, H.-P. Chan, and M. A. Helvie, " Comparison of similarity measures for the task of template matching of masses on serial mammograms.," Med. Phys. 32 (2), 515-529 (2005). 10.1118/1.1851892
104. S. Timp, S. van Engeland, and N. Karssemeijer, " A regional registration method to find corresponding mass lesions in temporal mammogram pairs.," Med. Phys. 32 (8), 2629-2638 (2005). 10.1118/1.1984323
105. P. R. Snoeren and N. Karssemeijer, " Gray scale registration of mammograms using a model of image acquisition.," Lecture Notes in Computer Science 2732, 401-412 (2003).
106. P. R. Snoeren and N. Karssemeijer, " Gray-scale and geometric registration of full-field digital and film-screen mammograms.," Med. Image Anal. 11 (2), 146-156 (2007). 10.1016/j.media.2006.11.003
107. S. van Engeland, P. Snoeren, J. Hendriks, and N. Karssemeijer, " A comparison of methods for mammogram registration.," IEEE Trans. Med. Imaging 22 (11), 1436-1444 (2003). 10.1109/TMI.2003.819273
108. 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 212 (3), 817-827 (1999). (Pubitemid 29410988)
109. Z. Huo, M. I. Giger, C. J. Vyborny, and C. E. Metz, " Breast cancer: Effectiveness of computer-aided diagnosis observer study with independent database of mammograms.," Radiology 224 (2), 560-568 (2002). 10.1148/radiol.2242010703 (Pubitemid 34809142)
110. Z. Huo, M. L. Giger, and C. J. Vyborny, " Computerized analysis of multiple-mammographic views: Potential usefulness of special view mammograms in computer-aided diagnosis.," IEEE Trans. Med. Imaging 20 (12), 1285-1292 (2001). 10.1109/42.974923
111. K. Drukker, K. Horsch, and M. L. Giger, " Multimodality computerized diagnosis of breast lesions using mammography and sonography.," Acad. Radiol. 12 (8), 970-979 (2005). 10.1016/j.acra.2005.04.014
112. K. Horsch, M. L. Giger, C. J. Vyborny, L. Lan, E. B. Mendelson, and R. E. Hendrick, " Classification of breast lesions with multimodality computer-aided diagnosis: Observer study results on an independent clinical data set.," Radiology 240 (2), 357-368 (2006). 10.1148/radiol.2401050208
113. S. van Engeland, S. Timp, and N. Karssemeijer, " Finding corresponding regions of interest in mediolateral oblique and craniocaudal mammographic views.," Med. Phys. 33 (9), 3203-3212 (2006). 10.1118/1.2230359
114. B. Liu, C. E. Metz, and Y. Jiang, " Effect of correlation on combining diagnostic information from two images of the same patient.," Med. Phys. 32 (11), 3329-3338 (2005). 10.1118/1.2064787
115. J. A. Baker, P. J. Kornguth, J. Y. Lo, M. E. Williford, and C. E. Floyd, " Breast cancer: Prediction with artificial neural network based on bi-rads standardized lexicon.," Radiology 196 (3), 817-822 (1995).
116. J. A. Baker, P. J. Kornguth, J. Y. Lo, and C. E. Floyd, " Artificial neural network: Improving the quality of breast biopsy recommendations.," Radiology 198 (1), 131-135 (1996). (Pubitemid 26008254)
117. J. Y. Lo, J. A. Baker, P. J. Kornguth, and C. E. Floyd, " Effect of patient history data on the prediction of breast cancer from mammographic findings with artificial neural networks.," Acad. Radiol. 6 (1), 10-15 (1999). 10.1016/S1076-6332(99)80056-7
118. M. K. Markey, J. Y. Lo, R. Vargas-Voracek, G. D. Tourassi, and C. E. Floyd, " Perceptron error surface analysis: A case study in breast cancer diagnosis.," Comput. Biol. Med. 32 (2), 99-109 (2002). 10.1016/S0010- 4825(01)00035-X
119. J. Y. Lo, M. K. Markey, J. A. Baker, and C. F. Floyd, " Cross-institutional evaluation of bi-rads predictive model for mammographic diagnosis of breast cancer.," AJR, Am. J. Roentgenol. 178 (2), 457-463 (2002). (Pubitemid 34098060)
120. M. K. Markey, G. D. Tourassi, M. Margolis, and D. M. DeLong, " Impact of missing data in evaluating artificial neural networks trained on complete data.," Comput. Biol. Med. 36 (5), 516-525 (2006). 10.1016/j.compbiomed.2005.02.001
121. C. E. Floyd, J. Y. Lo, and G. D. Tourassi, " Case-based reasoning computer algorithm that uses mammographic findings for breast biopsy decisions.," AJR, Am. J. Roentgenol. 175 (5), 1347-1352 (2000).
122. A. O. Bilska-Wolak and C. E. Floyd, " Development and evaluation of a case-based reasoning classifier for prediction of breast biopsy outcome with bi-rads lexicon.," Med. Phys. 29 (9), 2090-2100 (2002). 10.1118/1.1501140
123. A. O. Bilska-Wolak, C. E. Floyd, J. Y. Lo, and J. A. Baker, " Computer aid for decision to biopsy breast masses on mammography Validation on new cases.," Acad. Radiol. 12 (6), 671-680 (2005). 10.1016/j.acra.2005.02. 011
124. G. D. Tourassi, M. K. Markey, J. Y. Lo, and C. E. Floyd, " A neural network approach to breast cancer diagnosis as a constraint satisfaction problem.," Med. Phys. 28 (5), 804-811 (2001). 10.1118/1.1367861
125. E. A. Fischer, J. Y. Lo, and M. K. Markey, " Bayesian networks of BIRADS mark descriptors for breast lesion classification.," in Conference Proceedings of the IEEE Engineering in Medicine and Biology Society (IEEE Computer Society, Los Alamitos, 2004), Vol. 4, pp. 3031-3034. (Pubitemid 40035678)
126. M. Elter, R. Schulz-Wendtland, and T. Wittenberg, " The prediction of breast cancer biopsy outcomes using two cad approaches that both emphasize an intelligible decision process.," Med. Phys. 34 (11), 4164-4172 (2007). 10.1118/1.2786864
127. E. S. Burnside, J. E. Ochsner, K. J. Fowler, J. P. Fine, L. R. Salkowski, D. L. Rubin, and G. A. Sisney, " Use of microcalcification descriptors in bi-rads 4th edition to stratify risk of malignancy.," Radiology 242 (2), 388-395 (2007). 10.1148/radiol.2422052130
128. J. A. Baker, P. J. Kornguth, and C. E. Floyd, " Breast imaging reporting and data system standardized mammography lexicon: Observer variability in lesion description.," AJR, Am. J. Roentgenol. 166 (4), 773-778 (1996). (Pubitemid 126532715)
129. C. E. Metz, " Basic principles of roc analysis.," Semin Nucl. Med. 8 (4), 283-298 (1978). 10.1016/S0001-2998(78)80014-2 (Pubitemid 9075026)
130. C. E. Metz, B. A. Herman, and J. H. Shen, " Maximum likelihood estimation of receiver operating characteristic (roc) curves from continuously-distributed data.," Stat. Med. 17 (9), 1033-1053 (1998). 10.1002/(SICI)1097-0258(19980515)17:9<1033::AID-SIM784>3.0.CO;2-Z (Pubitemid 28203832)
131. E. E. Metz and X. Pan, " "Proper" binormal roc curves: Theory and maximum-likelihood estimation.," J. Math. Psychol. 43 (1), 1-33 (1999). 10.1006/jmps.1998.1218
132. D. C. Edwards, L. Lan, C. E. Metz, M. L. Giger, and R. M. Nishikawa, " Estimating three-class ideal observer decision variables for computerized detection and classification of mammographic mass lesions.," Med. Phys. 31 (1), 81-90 (2004). 10.1118/1.1631912
133. D. Guliato, R. M. Rangayyan, J. D. Carvalho, and S. A. Santiago, " Polygonal modeling of contours of breast tumors with the preservation of spicules.," IEEE Trans. Biomed. Eng. 55 (1), 14-20 (2008). 10.1109/TBME.2007.899310
134. P. Delogu, M. E. Fantacci, P. Kasae, and A. Retico, " Characterization of mammographic masses using a gradient-based segmentation algorithm and a neural classifier.," Comput. Biol. Med. 37 (10), 1479-1491 (2007). 10.1016/j.compbiomed.2007.01.009
135. A. Karahaliou, S. Skiadopoulos, I. Boniatis, P. Sakellaropoulos, E. Likaki, G. Panayiotakis, and L. Costaridou, " Texture analysis of tissue surrounding microcalcifications on mammograms for breast cancer diagnosis.," Br. J. Radiol. 80 (956), 648-656 (2007). 10.1259/bjr/30415751
136. I. Leichter, R. Lederman, S. S. Buchbinder, P. Bamberger, B. Novak, and S. Fields, " Computerized evaluation of mammographic lesions: What diagnostic role does the shape of the individual microcalcifications play compared with the geometry of the cluster?," AJR, Am. J. Roentgenol. 182 (3), 705-712 (2004). (Pubitemid 38269533)
137. S. S. Buchbinder, I. S. Leichter, P. N. Bamberger, B. Novak, R. Lederman, S. Fields, and D. J. Behar, " Analysis of clustered microcalcifications by using a single numeric classifier extracted from mammographic digital images.," Acad. Radiol. 5 (11), 779-784 (1998). 10.1016/S1076-6332(98) 80262-6
138. D. D. Dorfman, K. S. Berbaum, and C. E. Metz, " Roc rating analysis: generalization to the population of readers and cases with the jackknife method.," Invest. Radiol. 27, 723-731 (1992). 10.1097/00004424-199209000- 00015
139. Y. Jiang, R. M. Nishikawa, R. A. Schmidt, C. E. Metz, M. L. Giger, and K. Doi, " Improving breast cancer diagnosis with computer-aided diagnosis.," Acad. Radiol. 6 (1), 22-33 (1999). 10.1016/S1076-6332(99) 80058-0
140. Y. Jiang, R. M. Nishikawa, R. A. Schmidt, A. Y. Toledano, and K. Doi, " Potential of computer-aided diagnosis to reduce variability in radiologists' interpretations of mammograms depicting microcalcifications., " Radiology 220 (3), 787-794 (2001). 10.1148/radiol.220001257 (Pubitemid 32799991)
141. Y. Jiang, R. M. Nishikawa, R. A. Schmidt, and C. E. Metz, " Comparison of independent double readings and computer-aided diagnosis (cad) for the diagnosis of breast calcifications.," Acad. Radiol. 13 (1), 84-94 (2006). 10.1016/j.acra.2005.09.086
142. R. S. Rana, Y. Jiang, R. A. Schmidt, R. M. Nishikawa, and B. Liu, " Independent evaluation of computer classification of malignant and benign calcifications in full-field digital mammograms.," Acad. Radiol. 14 (3), 363-370 (2007). 10.1016/j.acra.2006.12.012
143. I. Leichter, S. Fields, R. Nirel, P. Bamberger, B. Novak, R. Lederman, and S. Buchbinder, " Improved mammographic interpretation of masses using computer-aided diagnosis.," Eur. Radiol. 10 (2), 377-383 (2000). 10.1007/s003300050059 (Pubitemid 30136843)
144. L. Hadjiiski, H.-P. Chan, B. Sahiner, M. A. Helvie, M. A. Roubidoux, C. Blane, C. Paramagul, N. Petrick, J. Bailey, K. Klein, M. Foster, S. Patterson, D. Adler, A. Nees, and J. Shen, " Improvement in radiologists' characterization of malignant and benign breast masses on serial mammograms with computer-aided diagnosis: An roc study.," Radiology 233 (1), 255-265 (2004). 10.1148/radiol.2331030432
145. L. Hadjiiski, B. Sahiner, M. A. Helvie, H.-P. Chan, M. A. Roubidoux, C. Paramagul, C. Blane, N. Petrick, J. Bailey, K. Klein, M. Foster, S. K. Patterson, D. Adler, A. V. Nees, and J. Shen, " Breast masses: Computer-aided diagnosis with serial mammograms.," Radiology 240 (2), 343-356 (2006). 10.1148/radiol.2401042099
146. J. Wei, L. M. Hadjiiski, B. Sahiner, H.-P. Chan, J. Ge, M. A. Roubidoux, M. A. Helvie, C. Zhou, Y.-T. Wu, C. Paramagul, and Y. Zhang, " Computer-aided detection systems for breast masses: Comparison of performances on full-field digital mammograms and digitized screen-film mammograms.," Acad. Radiol. 14 (6), 659-669 (2007). 10.1016/j.acra.2007.02.017