Classification for breast MRI using support vector machine

Proceedings - 8th IEEE International Conference on Computer and Information Technology Workshops, CIT Workshops 2008

Volumn , Issue , 2008, Pages 362-367

  Wang, Chuin Mu ^a   Mai, Xiao Xing ^a   Lin, Geng Cheng ^b   Kuo, Chio Tan ^a  

^a NATIONAL CHIN YI UNIVERSITY OF TECHNOLOGY   (Taiwan)

^b NATIONAL CENTRAL UNIVERSITY   (Taiwan)

Author keywords

[No Author keywords available]

Indexed keywords

ATOMS; CLASSIFICATION (OF INFORMATION); HISTOLOGY; IMAGE ANALYSIS; IMAGE CLASSIFICATION; IMAGE RETRIEVAL; IMAGING TECHNIQUES; INFORMATION TECHNOLOGY; LEARNING SYSTEMS; MAGNETIC FIELDS; MAGNETIC RESONANCE; MAGNETIC RESONANCE IMAGING; RESONANCE; TECHNOLOGY; VECTORS;

BREAST MRI; BREAST TUMORS; C-MEANS; CLASSIFICATION METHODS; CLASSIFICATION RESULTS; CLINICAL TRIALS; HUMAN BODIES; INTERNATIONAL CONFERENCES; MR IMAGING; MULTI-SPECTRAL; SUPPORT-VECTOR MACHINE;

SUPPORT VECTOR MACHINES;

EID: 52049093015     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CIT.2008.Workshops.90     Document Type: Conference Paper

References (17)

1. C.M. Wang, Sheng-Chi Yang, P.C. Chung, Y.N. Chung, C.C. Chen, Ching-Wen Yang, and Chia-Hsien Wen, "Orthogonal Subspace Projection-Base Approach to Classification of MR Image Sequences," Computerized Medical Imaging and Graphics, December, 2001, vol. 25, no. 6, pp. 465-476.
2. Newsweek, pp. 64, May 10, 1993.
3. D.J. Vyborny, "Can computers help radiologists read mammograms," Radiology 191, 1994, pp. 315-317.
4. D.B. Kopans, Breast Imaging 2/ed, Lippincott-Raven, 1998.
5. G. Cardenosa, Breast Imaging Companion 2/ed, Williams and Wilkins, 2001.
6. Y. Kita, E. Tohno, R.P. Highnam, and M. Brady, "A CAD system for the 3D location of lesions in mammograms", Medical Image Analysis, 2002, vol. 6, no. 3, pp. 267-273.
7. M.J. Stoutjesdijk, and C. Boetes, "Magnetic Resonance Imaging and Mammography in Women With a Hereditary Risk of Breast Cancer," Journal of the National Cancer Institute, July 18, 2001, vol. 93, no. 14, pp. 1095-1102.
8. rd Annual EMBS International Conference, 2001, vol. 3, pp. 2733-2736.
9. J. Li, N. Allinson, D. Tao, and X. Li, "Multitraining Support Vector Machine for Image Retrieval," IEEE Transaction on Image Processing, November, 2006, vol. 15, pp. 3597-3601.
10. M. Pontil, A. Verri, "Support vector machines for 3D object recognition", IEEE Transaction on PAMI, 1998, vol. 20, issue 6, pp.637-646.
11. A. Kumar, and D. Zhang, "Personal recognition using hand shape and texture," IEEE Transaction on Image Processing, August, 2006, vol. 15, issue. 8, pp. 2454-2461.
12. M. Brown, W. Grundy, D. Lin, N. Cristianini, C. Sugnet, T. Furey, M. Ares, and D. Haussler, "Knowledge-base analysis of microarray gene expression data using support vector machines", 1999, Technical report, University of California in Santa Cruz.
13. V.N. Vapnik, The Nature of Statistical Learning Theory, Springer-Verlag, NY, 1995.
14. V.N. Vapnik, Estimation of Dependences Based on Empirical Data, Springer-Verlag, NY, 1982.
15. R. Schalkoff, Pattern Recognition: Statistical, Structural and Neural Approaches, Wiley, NY, 1992.
16. Statistics announced of Department of Healthy of ROC, 2006.
17. C.M. Wang, C.C. Chen, Y.N. Chung, S.C. Yang, P.C. Chung, C.W. Yang, and C. I Chang, "Detection of Spectral Signatures in Multispectral MR Images for Classification," January, 2003, IEEE Transactions on Medical Imaging, vol.22, no. 1, pp.50-61.