Level set-based core segmentation of mammographic masses facilitating three stage (core, periphery, spiculation) analysis

Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings

Volumn , Issue , 2007, Pages 819-824

  Ball, John E ^a,b   Bruce, Lori Mann ^a,c  

^a IEEE

^b Navy Surface Warfare Center   (United States)

^c MISSISSIPPI STATE UNIVERSITY   (United States)

Author keywords

Breast cancer; CAD; Cancer; Chan vese; Computer aided detection; Digital mammography; Image segmentation; Level sets; Spiculations; Stellate lesions

Indexed keywords

COMPUTER AIDED DIAGNOSIS; DISCRIMINANT ANALYSIS; FEATURE EXTRACTION; MAMMOGRAPHY; MAXIMUM LIKELIHOOD; TUMORS;

BREAST CANCER; DIGITAL MAMMOGRAPHY; LEVEL SETS; STELLATE LESIONS;

IMAGE SEGMENTATION;

ARTICLE; BREAST TUMOR; FEMALE; HUMAN; IMAGE PROCESSING; MAMMOGRAPHY; METHODOLOGY; PREDICTIVE VALUE; RADIOGRAPHY;

BREAST NEOPLASMS; FEMALE; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MAMMOGRAPHY; PREDICTIVE VALUE OF TESTS;

EID: 57649211001     PISSN: 05891019     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IEMBS.2007.4352416     Document Type: Conference Paper

References (16)

1. National Cancer Institute, "National Cancer Institute Fact Sheet: Improving Methods for Breast Cancer Detection and Diagnosis," 2006. Available: http://www.cancer.gov/cancertopics/screening//breast.
2. A. Jemal, T. Murray, E. Ward, A. Samuels, R.C. Tiwari, A. Ghafoor, E.J. Feuer, and M.J. Thun, "Cancer Statistics, 2005," CA: A Cancer Journal for Clinicians, vol. 55, no. 1, pp. 10-30, 2005.
3. J.E. Ball, T.W. Butler, and L.M. Bruce, "Towards automated segmentation and classification of masses in mammograms," Proc. of the 26th Annual Intl. Conference of the Engineering in Medicine and Biology Society, San Francisco, CA, vol. 1, pp. 1814-1817, 2004.
4. J.E. Ball, "Three stage level set segmentation of mass core, periphery, and spiculations for automated image analysis of digital mammograms." Ph.D. in Electrical Engineering. Starkville, MS: Mississippi State Univ., May 2007.
5. J.A. Sethian, Level Set Methods and Fast Marching Methods: Evolving Interfaces in Computational Geometry, Fluid Mechanics, Computer Vision, and Materials Science, 2nd ed. Cambridge, UK: Cambridge University Press, 2002.
6. T.F. Chan and L.A. Vese, "Active contours without edges," IEEE Trans. on Image Processing, vol. 10, no. 2, pp. 266-277, 2001.
7. T. Chan and Z. Wei, "Level set based shape prior segmentation," Proc. of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 2, pp. 1164-1170, 20-25 Jun. 2005.
8. A. Tsai, A. Yezzi, Jr., W. Wells, C. Tempany, D. Tucker, A. Fan, W.E. Grimson, and A. Willsky, "A shape-based approach to the segmentation of medical imagery using level sets," IEEE Trans. on Medical Imaging, vol. 22, no. 2, pp. 137-154, Feb. 2003.
9. W. Ying, X. Xin-he, J. Tong, and Z. Da-zhe, "An Optimal Level Sets Method for Lung Nodules Detection in CT Images," Proc. of the Sixth Intl. Conference on Intelligent Systems Design and Applications, Jian, China, vol. 2, pp. 251-255, Oct. 2006.
10. M.F. Hansen, R. Larsen, B. Ersboll, and L.B. Christensen, "Coupled Shape Model Segmentation in Pig Carcasses," Proc. of the 18th International Conference on Pattern Recognition, vol. 1, pp. 468-471, 2006.
11. M. Heath, K.W. Bowyer, D. Kopans, W. Kegelmeyer, R. Moore, K. Chang, and S. Munishkumaran, "Current status of the Digital Database for Screening Mammography," in Digital Mammography, N. Karssemeijer, M. Thijssen, J. Hendriks, and L. van Erning, Eds. Boston, MA: Kluwer Academic Publishers, pp. 457-460, 1998.
12. R.O. Duda, P.E. Hart, and D.G. Stork, Pattern Classification, 2nd ed. New York: John Wiley & Sons, 2001.
13. V.P. Shah, L.M. Bruce, and N.H. Younan, "Applying modular classifiers to mammographic mass classification," Proc. of the 26th Annual Intl. Conference of the Engineering in Medicine and Biology Society (EMBC) vol. 3, pp. 1585-1588, Sept. 2004.
14. K. Laws, "Textured Image Segmentation." PhD in Electrical Engineering. Los Angeles, CA: Image Processing Institute, University of Southern California, Jan. 1980.
15. K. Laws, "Rapid Texture Identification," Proc. of the Image processing for missile guidance seminar, San Diego, CA, pp. 376-380, Jan. 1980.
16. M. Kallergi, "Medical Image Analysis Methods," in The Electrical Engineering and Applied Signal Processing Series, L. Costaridou, Ed. New York: Taylor & Francis, pp. 433-472, 2005.