Mammogram retrieval by similarity learning from experts

Proceedings - International Conference on Image Processing, ICIP

Volumn , Issue , 2006, Pages 2517-2520

  Wei, Liyang ^a   Yang, Yongyi ^a   Nishikawa, Robert M ^b   Wernick, Miles N ^a  

^a Illinois Institute of Technology   (United States)

^b UNIVERSITY OF CHICAGO   (United States)

Author keywords

Mammogram retrieval; Similarity learning

Indexed keywords

CONTENT BASED IMAGE RETRIEVAL; MAMMOGRAM RETRIEVAL; OBSERVER STUDIES; QUERY IMAGES; SIMILARITY LEARNING; SIMILARITY MEASURE;

IMAGE PROCESSING; IMAGING SYSTEMS; SUPERVISED LEARNING; X RAY SCREENS;

MAMMOGRAPHY;

EID: 70449662680     PISSN: 15224880     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICIP.2006.312805     Document Type: Conference Paper

References (16)

1. A. W. M. Smeulders, M. Worrings, S. Santini, et al, "Content-based image retrieval at the end of the early years," IEEE Trans. Patter Anal. Mach. Intell., vol. 22, no. 12, pp. 1349-1380, 2000.
2. H. Muller, N. Michoux, D. Bandon and A. Geissbuhler, "A review of content-based image retrieval system in medical applications - clinical benefits and future directions," International Journal of Medical inforniatics, vol. 73, pp. 1-23, 2004.
3. I El-Naqa, Y. Yang, N. P. Galatsanos, R. M. Nishikawa and M. N. Wernick, "A similarity learning approach to content based image retrieval: application to digital mammography," IEEE Trans. Medical Imaging, vol. 23, no. 10, pp. 1233-1244, 2004.
4. I El-Naqa, Y. Yang, N. P. Galatsanos, R. M. Nishikawa and M. N. Wernick, "Content-based image retrieval for digital mammography," IEEE international conference on inage processing, Rochester, NY, 2002.
5. W. Niblack, R. Barber, W. Equitz, et al, "Querying images by content, using color, texture, and shape," Proc. of SPIE, vol. 1908, pp. 173-187, 1993.
6. J. Hafner, H. S. Sawhney, W. Equitz, et al, "Efficient color histogram indexing for quadratic from distance functions, " IEEE Trans. Pattern. Mach. Intell, vol. 17, no. 7, pp. 729-736, 1995.
7. Y. Rubner, C. Tomasi, and L. J. Guibas, "A metric for distributions with applications to image databases," IEEE international conference on comnputer vision, India, 1998.
8. L. Wei, Y. Yang, R. M. Nishikawa "A study on several machine-learning methods for classification of malignant and benign clustered microcalcifications", IEEE Trans. Medical Imaging, vol. 24, no. 3, pp. 371-380, 2005.
9. R. M. Nishikawa, Y. Yang, etc, "Observers ability to judge the similarity of clustered microcalcifications on mammograms," Proc. of SPIE, vol. 5372, pp. 192-198, 2004.
10. V. Vapnik, Statistical learning theory, New York: Wiley, 1998.
11. Trevor Hastie and Robert Tibshirani, "Discriminant Adaptive Nearest Neighbor Classification," IEEE Trans. Pattern Anal. Mach. Intell, vol. 18, no. 6, pp. 607-616, 1996.
12. J. Shi and J. Malik, "Normalized cuts and image segmentation," IEEE Trans. Pattern Anal. Mach. Intell, vol. 22, no. 8, pp. 888-905, 2000.
13. Yixin Chen, James Z. Wang, and Robert Krovetz, "CLUE: cluster-based retrieval of images by unsupervised learning," IEEE Trans Imaae Processing vol. 14 no. 8 pp. 1187-1201 2005.
14. th Ed., 1970.
15. S. Theodoridis and K. Koutroumbas, Pattern Recognition, Academic press 2003
16. R. O. Duda and P E. Hart Pattcrn Classifcation and Scene Analysis. New York: Wiley, 1973.