Semiautomatic segmentation for the computer aided diagnosis of clustered microcalcifications

Progress in Biomedical Optics and Imaging - Proceedings of SPIE

Volumn 6915, Issue , 2008, Pages

  Elter, Matthias ^a   Held, Christian ^a  

^a FRAUNHOFER INSTITUTE FOR INTEGRATED CIRCUITS IIS   (Germany)

Author keywords

CADx; Computer aided diagnosis; Mammography; Microcalcifications; Segmentation; Semiautomatic; SVM

Indexed keywords

CLUSTER ANALYSIS; COMPUTER AIDED DIAGNOSIS; DATABASE SYSTEMS; MAMMOGRAPHY; ONCOLOGY; SUPPORT VECTOR MACHINES; TUMORS;

MICROCALCIFICATIONS; SEMIAUTOMATIC;

IMAGE SEGMENTATION;

EID: 44349087478     PISSN: 16057422     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.770146     Document Type: Conference Paper

References (32)

1. A. C. Society, "Breast cancer facts & figures 2007-2008." Atlanta: American Cancer Society, inc., 2007.
2. American College of Radiology, Breast Imaging Reporting and Data System (BI-RADS©) Atlas, 2006.
3. 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, pp. 1840-1850, Dec 2004.
4. D. B. Kopans, "The positive predictive value of mammography," Am J Roentgenol 158, pp. 521-526, 1992.
5. 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, pp. 671-678, Mar 1996.
6. 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, pp. 371-380, Mar 2005.
7. T. Ema, K. Doi, R. M. Nishikawa, Y. Jiang, and J. Papaioannou, "Image feature analysis and computer-aided diagnosis in mammography: reduction of false-positive clustered microcalcifications using local edge-gradient analysis.," Med Phys 22, pp. 161-169, Feb 1995.
8. 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, pp. 549-567, Mar 1997.
9. 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, pp. 2007-2019, Oct 1998.
10. 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, pp. 2600-2608, Nov 2000.
11. 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, pp. 789-799, Apr 2004.
12. M. Kallergi, "Computer-aided diagnosis of mammographic microcalcification clusters.," Med Phys 31, pp. 314-326, Feb 2004.
13. 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, pp. 141-150, Jun 2005.
14. 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, pp. 4164-4172, Nov 2007.
15. M. Heath, K. Bowyer, D. Kopans, R. Moore, and P. Kegelmeyer, "The digital database for screening mammography," The Proceedings of the 5th International Workshop on Digital Mammography , 2000.
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, pp. 1247-1254, Aug 1995.
17. R. N. Strickland and H. I. Hahn, "Wavelet tranforms for detecting microcalcifications in mammograms," IEEE Transactions on Medical Imaging 15(2), pp. 218-229, 1996.
18. T. C. Wang and N. B. Karayiannis, "Detection of microcalcifications in digital mammograms using wavelets.," IEEE Trans Med Imaging 17, pp. 498-509, Aug 1998.
19. 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, pp. 949-956, Jun 1998.
20. M. J. Lado, P. G. Tahoces, A. J. Mndez, M. Souto, and J. J. Vidal, "A wavelet-based algorithm for detecting clustered microcalcifications in digital mammograms.," Med Phys 26, pp. 1294-1305, Jul 1999.
21. S. Yu and L. Guan, "A CAD system for the automatic detection of clustered microcalcifications in digitized mammogram films.," IEEE Trans Med Imaging 19, pp. 115-126, Feb 2000.
22. P. Heinlein, J. Drexl, and W. Schneider, "Integrated wavelets for enhancement of microcalcifications in digital mammography.," IEEE Trans Med Imaging 22, pp. 402-413, Mar 2003.
23. G. Lemaur, K. Drouiche, and J. DeConinck, "Highly regular wavelets for the detection of clustered microcalcifications in mammograms.," IEEE Trans Med Imaging 22, pp. 393-401, Mar 2003.
24. 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, pp. 2206-2219, Jun 2007.
25. I. Daubechies, Ten lectures on wavelets, SIAM, Philadelphia, PA, 1992.
26. M. Hu, "Visual pattern recognition by moment invariants.," IRE Trans. on Information Theory IT-8, pp. 179-187, 1962.
27. J. Wood, "Invariant pattern recognition: A review.," Pattern Recognition 29(1), pp. 1-17, 1996.
28. H. Vafaie and K. D. Jong, "Genetic algorithms as a tool for feature selection in machine learning," in Proceedings of the 4th International Conference on Tools with Artificial Intelligence, pp. 200-204, IEEE Computer Society Press, (Arlington, VA, USA), 1992.
29. C. Cortes and V. Vapnik, "Support-vector networks," Machine Learning 20(3), pp. 273-297, 1995.
30. L. Lusted, "Signal detectability and medical decision-making," Science 171, pp. 1217-1219, 1971.
31. J. Egan, Signal Detection Theory and ROC Analysis, Academic Press, New York, 1975.
32. C. E. Metz, B. A. Herman, and J. H. Shen, "Maximum-likelihood estimation of roc curves from continuously-distributed data.," Stat Med 17, pp. 1033-1053, 1998.