A novel approach to mass abnormality detection in mammographic images

Proceedings of the 3rd IASTED International Conference on Biomedical Engineering 2005

Volumn , Issue , 2005, Pages 180-185

  Guo, Qi ^a   Ruiz, Virginie ^a   Shao, Jiaqing ^b   Guo, Falei ^c  

^a UNIVERSITY OF READING   (United Kingdom)

^b UNIVERSITY OF KENT   (United Kingdom)

^c NONE   (China)

Author keywords

Hausdorff dimension; Mammogram; Mass; Support vector machine

Indexed keywords

FEATURE EXTRACTION; IMAGE ANALYSIS; LEARNING SYSTEMS; MAMMOGRAPHY; STATISTICAL METHODS; TUMORS;

HAUSDORFF DIMENSION; MAMMOGRAMS; MASS; SUPPORT VECTOR MACHINES (SVM);

MEDICAL IMAGING;

EID: 27844568672     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (13)

1. Cancer Research UK, http://www.cancerresearchuk.org/images/11632/ briefsheet_breast.pdf, 2003.
2. M. L. Giger, Z. Huo, M. A. Kupinski, & C. J. Vyborny, Computer-aided Diagnosis in Mammography, in M. Sonka & J. M. Fitzzpatrick, (eds.), Handbook of Medical Imaging, 2, SPIE, 2000, 915-1004.
3. A. Laine, S. Song, J. Fan, W. Huda, & J. Honeyman, Adaptive multiscale processing for contrast enhancement, Proc. SPIE, 1905, 1993, 521-532.
4. Z. Huo, M. L. Giger, C. J. Vyborny, U. Bick, P. Lu, D. E. Wolverton, & R. A. Schmidt, Analysis of spiculation in the computerised classification of mammographic masses, Med Phys, 22, 1995, 1569-1579.
5. M. A. Kupinski, & M. L. Giger, Feature selection with limited datasets, Med Phys, 26, 1999, 2176-2182.
6. S-M. Lai, X. Li., & W. F. Bischof, On techniques for detecting circumscribed masses in mammograms, IEEE Trans. on Medical Imaging, 8(4), 1989, 377-386.
7. D. Brzakovic, X. M. Luo, & P. Brzakovic, An approach to automated detection of tumours in mammograms, IEEE Trans. on Medical Imaging, 9(3), 1990, 233-241.
8. B. B. Mandelbrot, The fractal geometry of nature (NY: Freeman, 1983).
9. V. Vapnik, Statistical learning theory (NY: Wiley, 1998).
10. K. R. Muller, S. Mika, G. Ratsch, K. Tsuda, & B. Scholkopf, An introduction to kernel-based learning algorithms, IEEE Trans. Neural Networks, 12, 2001, 181-201.
11. I. El-Naqa, Y. Yang., M. N. Wernick, N. P. Galatsanos, & R. M. Nishikawa, A Support Vector Machine Approach for Detection of Microcalcifications, IEEE Trans. on Medical Imaging, 21(12), 2002, 1552-1563.
12. K. Falconer, Fractal geometry - mathematical foundations and applications (NY: Wiley, 1990).
13. nd International Workshop on Digital Mammography, Excerpta Medica, International Congress Series 1069, York, England, 1994, 315-324.