Dual system approach to computer-aided detection of breast masses on mammograms

Medical Physics

Volumn 33, Issue 11, 2006, Pages 4157-4168

  Wei, Jun ^a   Chan, Heang Ping ^a   Sahiner, Berkman ^a   Hadjiiski, Lubomir M ^a   Helvie, Mark A ^a   Roubidoux, Marilyn A ^a   Zhou, Chuan ^a   Ge, Jun ^a  

^a UNIVERSITY OF MICHIGAN MEDICAL SCHOOL   (United States)

Author keywords

Artificial neural network (ANN); Computer aided detection (CAD); Dual system; Mammogram; Mass detection

Indexed keywords

BACKPROPAGATION; COMPUTER AIDED NETWORK ANALYSIS; DISCRIMINANT ANALYSIS; IMAGE SEGMENTATION; MAMMOGRAPHY; NEURAL NETWORKS; OBJECT DETECTION; STATISTICAL TESTS; TEXTURES; X RAY SCREENS;

COMPUTER-AIDED DETECTION; DUAL SYSTEM; FEEDFORWARD BACKPROPAGATION; FREE-RESPONSE RECEIVERS; LINEAR DISCRIMINANT ANALYSIS; MAMMOGRAM; MASS DETECTION; TEXTURE FEATURE EXTRACTION;

COMPUTER AIDED DIAGNOSIS;

ARTICLE; ARTIFICIAL NEURAL NETWORK; BREAST TUMOR; COMPUTER AIDED DESIGN; CONTROLLED STUDY; HUMAN; IMAGE ANALYSIS; MAJOR CLINICAL STUDY; MAMMOGRAPHY; METHODOLOGY; MORPHOLOGY; PRIORITY JOURNAL; SENSITIVITY ANALYSIS; STATISTICAL ANALYSIS; TUMOR DIAGNOSIS; TUMOR LOCALIZATION; TUMOR VOLUME; VALIDATION STUDY;

EID: 33750545794     PISSN: 00942405     EISSN: None     Source Type: Journal    
DOI: 10.1118/1.2357838     Document Type: Article

References (54)

1. American Cancer Society, www.cancer.org, " Statistics for 2005.. "
2. C. R. Smart, R. E. Hendrick, J. H. Rutledge, and R. A. Smith, " Benefit of mammography screening in women ages 40 to 49 years: Current evidence from randomized controlled trials., " Cancer 75, 1619-1626 (1995).
3. S. A. Feig, C. J. D'Orsi, R. E. Hendrick, V. P. Jackson, D. B. Kopans, B. Monsees, E. A. Sickles, C. B. Stelling, M. Zinninger, and P. Wilcox-Buchalla, " American College of Radiology guidelines for breast cancer screening., " AJR, Am. J. Roentgenol. 171, 29-33 (1998).
4. B. Cady and J. S. Michaelson, " The life-sparing potential of mammographic screening., " Cancer 91, 1699-1703 (2001).
5. H. C. Zuckerman, " The role of mammography in the diagnosis of breast cancer., " in Breast Cancer, Diagnosis and Treatment, edited by, I. M. Ariel, and, J. B. Cleary, (McGraw-Hill, New York, 1987).
6. F. Shtern, C. Stelling, B. Goldberg, and R. Hawkins, " Novel technologies in breast imaging: National Cancer Institute perspective., " Orlando, FL.
7. C. J. Vyborny, " Can computers help radiologists read mammograms?, " Radiology 191, 315-317 (1994).
8. T. W. Freer and M. J. Ulissey, " Screening mammography with computer-aided detection: Prospective study of 12,860 patients in a community breast center., " Radiology 220, 781-786 (2001).
9. M. A. Helvie, L. M. Hadjiiski, E. Makariou, H. P. Chan, N. Petrick, B. Sahiner, S. C. B. Lo, M. Freedman, D. Adler, J. Bailey, " Sensitivity of noncommercial computer-aided detection system for mammographic breast cancer detection-A pilot clinical trial., " Radiology 231, 208-214 (2004).
10. R. L. Birdwell, P. Bandodkar, and D. M. Ikeda, " Computer-aided detection with screening mammography in a university hospital setting., " Radiology 236, 451-457 (2005).
11. D. Gur, J. H. Sumkin, H. E. Rockette, M. A. Ganott, C. Hakim, L. A. Hardesty, W. R. Poller, R. Shah, and L. Wallace, " Changes in breast cancer detection and mammography recall rates after the introduction of a computer-aided detection system., " J. Natl. Cancer Inst. 96, 185-190 (2004).
12. S. A. Feig, E. A. Sickles, W. P. Evans, and M. N. Linver, " Re. Changes in breast cancer detection and mammography recall rates after the introduction of a computer-aided detection system., " J. Natl. Cancer Inst. 96, 1260-1261 (2004).
13. T. E. Cupples, " Impact of computer-aided detection (CAD) in a regional screening mammography program., " Radiology 221 (P), 520 (2001).
14. S. L. Ng and W. F. Bischof, " Automated detection and classification of breast tumors., " Comput. Biomed. Res. 25, 218-237 (1992).
15. N. Petrick, H. P. Chan, D. Wei, B. Sahiner, M. A. Helvie, and D. D. Adler, " Automated detection of breast masses on mammograms using adaptive contrast enhancement and texture classification., " Med. Phys. 23, 1685-1696 (1996).
16. B. Zheng, Y. H. Chang, and D. Gur, " Computerized detection of masses in digitized mammograms using single-image segmentation and a multilayer topographic feature analysis., " Acad. Radiol. 2, 959-966 (1995).
17. N. Karssemeijer and G. te Brake, " Detection of stellate distortions in mammograms., " IEEE Trans. Med. Imaging 15, 611-619 (1996).
18. H. Kobatake and Y. Yoshinaga, " Detection of spicules on mammogram based on skeleton analysis., " IEEE Trans. Med. Imaging 15, 235-245 (1996).
19. Z. M. 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, 155-168 (1998).
20. W. Qian, L. H. Li, and L. P. Clarke, " Image feature extraction for mass detection in digital mammography: Influence of wavelet analysis., " Med. Phys. 26, 402-408 (1999).
21. N. Petrick, H. P. Chan, B. Sahiner, M. A. Helvie, S. Paquerault, and L. M. Hadjiiski, " Breast cancer detection: Evalution of a mass detection algorithm for computer-aided diagnosis: Experience in 263 patients., " Radiology 224, 217-224 (2002).
22. S. Paquerault, N. Petrick, H. P. Chan, B. Sahiner, and M. A. Helvie, " Improvement of computerized mass detection on mammograms: Fusion of two-view information., " Med. Phys. 29, 238-247 (2002).
23. B. Zheng, W. F. Good, D. R. Armfield, C. Cohen, T. Hertzberg, J. H. Sumkin, and D. Gur, " Performance change of mammographic CAD schemes optimized with most-recent and prior image databases., " Acad. Radiol. 10, 283-288 (2003).
24. J. Wei, B. Sahiner, L. M. Hadjiiski, H. P. Chan, N. Petrick, M. A. Helvie, M. A. Roubidoux, J. Ge, and C. Zhou, " Computer aided detection of breast masses on full field digital mammograms., " Med. Phys. 32, 2827-2838 (2005).
25. N. Petrick, H. P. Chan, B. Sahiner, M. A. Helvie, and S. Paquerault, " Evaluation of an automated computer-aided diagnosis system for the detection of masses on prior mammograms., " San Diego, 2000.
26. G. M. Te Brake, N. Karssemeijer, and J. Hendriks, " Automated detection of breast carcinomas not detected in a screening program., " Radiology 207, 465-471 (1998).
27. D. M. Ikeda, R. L. Birdwell, K. F. O'Shaughnessy, E. A. Sickles, and R. J. Brenner, " Computer-aided detection output on 172 subtle findings on normal mammograms previously obtained in women with breast cancer detected at follow-up screening mammography., " Radiology 230, 811-819 (2004).
28. D. Gur, J. S. Stalder, L. A. Hardesty, B. Zheng, J. H. Sumkin, D. M. Chough, B. E. Shindel, and H. E. Rockette, " Computer-aided detection performance in mammographic examination of masses: Assessment., " Radiology 233, 418-423 (2004).
29. H. El-Shishini, M. S. Abdel-mottaleb, M. El-Raey, and A. Shoukry, " A multistage algorithm for fast classification of patterns., " Pattern Recogn. Lett. 10, 211-215 (1989).
30. J. Y. Zhou and T. Pavlidis, " Discrimination of characters by a multi-stage recognition process., " Pattern Recogn. 27, 1539-1549 (1994).
31. L. K. Hansen and P. Salamon, " Neural network ensembles., " IEEE Trans. Pattern Anal. Mach. Intell. 12, 993-1001 (1990).
32. G. Rogova, " Combining the results of several neural network classifiers., " Neural Networks 7, 777-781 (1994).
33. S. Hashem and B. Schmeiser, " Improving model accuracy using optimal linear combinations of trained neural networks., " IEEE Trans Neural Networks 6, 792-794 (1995).
34. T. K. Ho, J. J. Hull, and S. N. Srihari, " Decision combination in multiple classifier systems., " IEEE Trans. Pattern Anal. Mach. Intell. 16, 66-75 (1994).
35. D. A. Bell, J. W. Guan, and Y. Bi, " On combining classifier mass functions for text categorization., " IEEE Trans. Knowl. Data Eng. 17, 1307-1319 (2005).
36. J. Cao, M. Ahmadi, and M. Shridhar, " Recognition of handwritten numerals with multiple feature and multistage classifier., " Pattern Recogn. 28, 153-160 (1995).
37. A. Al-Ani and M. Deriche, " A new technique for combining multiple classifiers using the Dempster-Shafer theory of evidence., " J. Artif. Intell. Res. 17, 333-361 (2002).
38. J. Wei, B. Sahiner, L. M. Hadjiiski, H. P. Chan, M. A. Helvie, and M. A. Roubidoux, " A dual computer-aided detection (CAD) system for improvement of mass detection on mammograms., " RSNA Program Book 2004, p. 491.
39. J. Wei, B. Sahiner, L. M. Hadjiiski, H. P. Chan, M. A. Helvie, M. A. Roubidoux, N. Petrick, C. Zhou, and J. Ge, " Computer aided detection of breast masses on mammograms: Performance improvement using a dual system., " Proc. SPIE 5747, 9-15 (2005).
40. J. Wei, B. Sahiner, L. M. Hadjiiski, H. P. Chan, N. Petrick, M. A. Helvie, C. Zhou, and Z. Ge, " Computer aided detection of breast masses on full-field digital mammograms: False positive reduction using gradient field analysis., " Proc. SPIE 5370, 992-998 (2004).
41. 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, 1642-1654 (1999).
42. D. Wei, H. P. Chan, N. Petrick, B. Sahiner, M. A. Helvie, D. D. Adler, and M. M. Goodsitt, " False-positive reduction technique for detection of masses on digital mammograms: Global and local multiresolution texture analysis., " Med. Phys. 24, 903-914 (1997).
43. M. M. Galloway, " Texture classification using gray level run lengths., " Comput. Graph. Image Process. 4, 172-179 (1975).
44. M. J. Norusis, SPSS for Windows Release 6 Professional Statistics (SPSS, Chicago, IL, 1993).
45. L. M. Hadjiiski, B. Sahiner, H. P. Chan, N. Petrick, M. A. Helvie, and M. N. Gurcan, " Analysis of temporal change of mammographic features: Computer-aided classification of malignant and benign breast masses., " Med. Phys. 28, 2309-2317 (2001).
46. 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, 1033-1053 (1998).
47. B. Sahiner, H. P. Chan, N. Petrick, R. F. Wagner, and L. M. Hadjiiski, " Feature selection and classifier performance in computer-aided diagnosis: The effect of finite sample size.., " Med. Phys. 27, 1509-1522 (2000).
48. C. M. Bishop, Neural Networks for Pattern Recognition (Clarendon, Oxford, 1995).
49. J. A. Freeman and D. M. Skapura, Neural Networks-Algorithms, Applications, and Programming Techniques (Addison-Wesley, Reading, 1991).
50. D. P. Chakraborty and L. H. L. Winter, " Free-response methodology: Alternate analysis and a new observer-performance experiment., " Radiology 174, 873-881 (1990).
51. D. P. Chakraborty and K. S. Berbaum, " Observer studies involving detection and localization: Modeling, analysis, and validation., " Med. Phys. 31, 2313-2330 (2004).
52. K. F. O'Shaughnessy, R. A. Castellino, S. L. Muller, and K. Benali, " Computer-aided detection (CAD) on 90 biopsy-proven breast cancer cases acquired on a full-field digital mammography (FFDM) system., " Radiology 221 (P), 471 (2001).
53. L. J. Warren Burhenne, S. A. Wood, C. J. D'Orsi, S. A. Feig, D. B. Kopans, K. F. O'Shaughnessy, E. A. Sickles, L. Tabar, C. J. Vyborny, and R. A. Castellino, " Potential contribution of computer-aided detection to the sensitivity of screening mammography., " Radiology 215, 554-562 (2000).
54. R. E. Brem, J. W. Hoffmeister, J. A. Rapelyea, G. Zisman, K. Mohtashemi, G. Jindal, M. P. DiSimio, and S. K. Rogers, " Impact of breast density on computer-aided detection for breast cancer., " AJR, Am. J. Roentgenol. 184, 439-444 (2005).