A similarity learning approach to content-based image retrieval: Application to digital mammography

IEEE Transactions on Medical Imaging

Volumn 23, Issue 10, 2004, Pages 1233-1244

  El Naqa, Issam ^a   Yang, Yongyi ^b   Galatsanos, Nikolas P ^c   Nishikawa, Robert M ^d   Wernick, Miles N ^b  

^a WASHINGTON UNIVERSITY   (United States)

^b Illinois Institute of Technology   (United States)

^c UNIVERSITY OF IOANNINA   (Greece)

^d UNIVERSITY OF CHICAGO   (United States)

Author keywords

Computer aided diagnosis; Content based image retrieval; Digital radiography; Kernel methods; Mammogram; Relevance feedback

Indexed keywords

DATABASE SYSTEMS; FEEDBACK; IMAGE RETRIEVAL; MEDICAL IMAGING; NEURAL NETWORKS; PROFESSIONAL ASPECTS; RADIOGRAPHY; STUDENTS;

COMPUTER-AIDED DIAGNOSIS; CONTENT-BASED IMAGE RETRIEVAL; KERNEL METHODS; RELEVANCE FEEDBACK;

MAMMOGRAPHY;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BREAST DISEASE; CALCINOSIS; CLINICAL TRIAL; CLUSTER ANALYSIS; COMPARATIVE STUDY; COMPUTER ASSISTED DIAGNOSIS; COMPUTER GRAPHICS; COMPUTER INTERFACE; COMPUTER SIMULATION; DATA BASE; DECISION SUPPORT SYSTEM; FEMALE; HUMAN; IMAGE QUALITY; IMAGE SUBTRACTION; INFORMATION RETRIEVAL; MAMMOGRAPHY; MATHEMATICAL COMPUTING; METHODOLOGY; PRECANCER; RADIOGRAPHY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING; VALIDATION STUDY;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BREAST DISEASES; CALCINOSIS; CLUSTER ANALYSIS; COMPUTER GRAPHICS; COMPUTER SIMULATION; DATABASE MANAGEMENT SYSTEMS; DECISION SUPPORT SYSTEMS, CLINICAL; FEMALE; HUMANS; INFORMATION STORAGE AND RETRIEVAL; MAMMOGRAPHY; NUMERICAL ANALYSIS, COMPUTER-ASSISTED; PATTERN RECOGNITION, AUTOMATED; PRECANCEROUS CONDITIONS; RADIOGRAPHIC IMAGE ENHANCEMENT; RADIOGRAPHIC IMAGE INTERPRETATION, COMPUTER-ASSISTED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING, COMPUTER-ASSISTED; SUBTRACTION TECHNIQUE; USER-COMPUTER INTERFACE;

EID: 6344285519     PISSN: 02780062     EISSN: None     Source Type: Journal    
DOI: 10.1109/TMI.2004.834601     Document Type: Article

References (41)

1. A. D. Bimbo, Visual Information Retrieval. San Mateo, CA: Morgan Kauffman Publishers, 1999.
2. Y. Rui and T. Huang, "Image retrieval: current techniques, promising directions and open issues," J. Visual Commun. Image Representation, vol. 10, pp. 39-62, 1999.
3. T. Kato, T. Kurita, N. Otsu, and K. Hirata, "A sketch retrieval method for full color image database," in Proc. 11th Int. Conf. Pattern Recogn., The Hague, The Netherlands, 1992, pp. 530-533.
4. W. Niblack, R. Barber, W. Equitz, M. Flickner, E. Glasman, D. Petkovic, P. Yanker, and C. Faloutsos, "The QBIC project: querying images by content using color, texture, and shape," SPIE Proc. Storage Retrieval Image Video Databases, vol. 1908, pp. 137-146, 1993.
5. S. Wong, "CBIR in medicine: still a long way to go," in Proc. IEEE Workshop Content-Based Access of Image and Video Libraries, Santa Barbara, CA, June 1998, p. 115.
6. H. A. Swett and P. L. Miller, "ICON: a computer-based approach to differential diagnosis in radiology," Radiology, vol. 163, pp. 555-558, 1987.
7. P. M. Kelly and T. M. Cannon, "CANDID: comparison algorithm for navigating digital image databases," in Proc. Int. Working Conf. Scientific and Statistical Database Management, 1994, pp. 252-258.
8. A. Guimond and G. Subsol, "Automatic MRI database exploration and applications," Pattern Recogn. Artif. Intell., vol. 11, no. 8, pp. 1345-1365, 1997.
9. Y. Liu and F. Dellaert, "A classification based similarity metric for 3D image retrieval," in Proc. IEEE Computer Society Conf. Computer Vision and Pattern Recognition, 1998, pp. 800-805.
10. J. Sklansky, E. Tao, M. Bazargan, C. Ornes, R. Murchison, and S. Teklehaimanot, "Computer-aided, case-based diagnosis of mammographic regions of interest containing microcalcifications," Academic Radiol., vol. 7, no. 6, pp. 395-406, 2000.
11. C. Ornes and J. Sklansky, "A visual neural classifier," IEEE Trans. Systems, Man, and Cybernetics, pt. B, vol. 28, pp. 620-625, 1998.
12. Y. Kawata, N. Niki, H. Ohmatsu, M. Kusumoto, R. Kakinuma, K. Mori, H. Nishiyama, K. Eguchi, M. Kaneko, and N. Moriyama, "Three-dimensional CT image retrieval in a database of pulmonary nodules," in Proc. of IEEE International Conference on Image Processing, Rochester, NY, Sept. 2002, pp. 149-152.
13. I. El-Naqa, M. N. Wernick, Y. Yang, and N. P. Galatsanos, "Image retrieval based on similarity learning," in Proc. IEEE Int. Conf. Image Processing, Vancouver, BC, Canada, 2000, pp. 722-725.
14. A. I. Mushlin, R. W. Kouides, and D. E. Shapiro, "Estimating the accuracy of screening mammography: a meta-analysis," Amer. J. Preventive Med., vol. 14, no. 2, pp. 143-153, 1998.
15. R. N. Strickland and H. L. Hahn, "Wavelet transforms for detecting microcalciflcations in mammograms," IEEE Trans. Med. Imag., vol. 15, no. 2, pp. 218-229, 1996.
16. E. A. Sickles, "Mammographic features of 300 consecutive nonpalpable breast cancers," Amer. J. Roentgenol., vol. 146, pp. 661-663, 1986.
17. D. B. Kopans, "The positive predictive value of mammography," Amer. J. Roentgenol., vol. 158, pp. 521-526, 1992.
18. J. G. Elmore, C. K. Wells, C. H. Lee, D. H. Howard, and A. R. Feinstein, "Variability in radiologists' interpretations of mammograms," New Engl. J. Med., vol. 331, no. 22, pp. 1493-1499, 1994.
19. R. M. Nishikawa, M. L. Giger, K. Doi, C. J. Vyborny, and R. A. Schmidt, "Computer aided detection of clustered microcalcifications in digital mammograms," Med. Biological Eng. Computing, vol. 33, pp. 174-178, 1995.
20. P. L. Miller, "Critiquing anesthetic management: the "ATTENDING" computer system," Anesthesiology, vol. 58, pp. 362-369, 1983.
21. B. Ripley, Pattern Recognition Neural Networks. Cambridge, U.K.: Cambridge Univ. Press, 1996.
22. V. Vapnik, Statistical Learning Theory. New York: Wiley, 1998.
23. M. Pontil and A. Verri, "Support vector machines for 3-D object recognition," IEEE Trans. Pattern Anal. Machine Intell., vol. 20, pp. 637-646, June 1998.
24. V. Wan and W. M. Campbell, "Support vector machines for speaker verification and identification," in Proc. IEEE Workshop Neural Networks for Signal Processing, Sydney, Australia, Dec. 2000, pp. 775-784.
25. E. Osuna, R. Freund, and F. Girosi, "Training support vector machines: application to face detection," in Proc. Computer Vision and Pattern Recognition, Puerto Rico, 1997, pp. 130-136.
26. T. Joachims, "Transductive inference for text classification using support vector machines," in Proc. Int. Conf. Machine Learning, Slovenia, June 1999.
27. C. J. Burges, "A tutorial on support vector machines for pattern recognition," Data Mining and Knowledge Discovery, vol. 2, no. 2, pp. 121-167, 1998.
28. I. El-Naqa, Y. Yang, M. N. Wernick, N. P. Galatsanos, and R. M. Nishikawa, "A support vector machine for approach for detection of microcalcifications," IEEE Trans. Med. Imag., vol. 21, pp. 1552-1563, Dec. 2002.
29. D. F. Specht, "A general regression neural network," IEEE Trans. Neural Network, vol. 2, pp. 568-576, Nov. 1991.
30. Y. Rui, T. Huang, M. Ortega, and S. Mehrotra, "Relevance feedback: a power tool for interactive content-based image retrieval," IEEE Trans. Circuits Syst. Video Technol., vol. 8, Sept. 1998.
31. I. El-Naqa, Y. Yang, N. P. Galatsanos, and M. N. Wernick, "Relevance feedback based on incremental learning for mammogram retrieval," in Proc. IEEE Int. Conf. Image Processing, Barcelona, Spain, Sept. 13-17, 2003.
32. Illustrated Breast Imaging Reporting and Data System, 3rd ed. Reston, VA: American College of Radiology, 1998.
33. M. G. Kendall, Rank Correlation Methods, 4th ed. London, U.K.: Griffin, 1970.
34. J. H. Zar, Biostatistical Analysis, 2nd ed, Englewood Cliffs, NJ: Prentice-Hall, 1984.
35. 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, vol. 198, pp. 671-678, 1996.
36. Y. Jiang, R. M. Nishikawa, R. Schmidt, C. Metz, M. L. Giger, and K. Doi, "Improving" breast cancer diagnosis with computer aided diagnosis," Acad Radiol, vol. 6, pp. 22-33, 1999.
37. S. Liang, R. Rangayyan, and J. E. Desautels, "Application of shape analysis to mammographic Calcifications," IEEE Trans. Med. Imag., vol. 13, pp. 263-274, June 1994.
38. S. Theodoridis and K. Koutroumbas, Pattern Recognition, 2nd ed. New York: Academic, 2003.
39. R. C. Gonzalez and R. E. Woods, Digital Image Processing. Reading, MA: Addison-Wesley, 1992.
40. R. Kennedy, Y. Lee, B. Van Roy, C. D. Reed, and R. P. Lippman, Solving Data Mining Problems Through Pattern Recognition. Englewood Cliffs, NJ: Prentice-Hall, 1998.
41. M. Hollander and D. A. Wolfe, Nonparametric Statistical Methods. New York: Wiley, 1972.