A dual-stage method for lesion segmentation on digital mammograms

Medical Physics

Volumn 34, Issue 11, 2007, Pages 4180-4193

  Yuan, Yading ^a   Giger, Maryellen L ^a   Li, Hui ^a   Suzuki, Kenji ^a   Sennett, Charlene ^a  

^a UNIVERSITY OF CHICAGO   (United States)

Author keywords

Breast cancer; Computer aided diagnosis; Geometric active contour model; Mass lesion segmentation

Indexed keywords

COMPUTER AIDED DIAGNOSIS; MAMMOGRAPHY; X RAY SCREENS;

BACKGROUND ESTIMATION; BREAST CANCER; COMPUTATIONALLY EFFICIENT; FULL FIELD DIGITAL MAMMOGRAPHY; GEOMETRIC ACTIVE CONTOURS; MASS LESION; RADIAL GRADIENT INDICES; REGION GROWING METHODS;

IMAGE SEGMENTATION;

ALGORITHM; ARTICLE; BREAST LESION; CONTROLLED STUDY; DATA BASE; DIGITAL IMAGING; DIGITAL MAMMOGRAPHY; HUMAN; IMAGING SYSTEM; INTERFEROMETRY; MAMMOGRAPHY; PARENCHYMA; PRIORITY JOURNAL; RADIOLOGIST; STATISTICAL SIGNIFICANCE; TISSUE HOMOGENATE;

EID: 35648984504     PISSN: 00942405     EISSN: None     Source Type: Journal    
DOI: 10.1118/1.2790837     Document Type: Article

References (35)

1. A. J. Jemal, R. Siegel, E. Ward, T. Murray, J. Xu, and M. J. Thun, " Cancer statistics, 2007., " Ca-Cancer J. Clin. 57, 43-66 (2007).
2. G. M. Newstead, " Role of MR in breast imaging., " In RSNA Categorical Course in Breast Imaging (Chicago, 1999), pp. 287-293.
3. S. G. Orel and M. D. Schnall, " MR imaging of the breast for the detection, diagnosis, and staging of breast cancer., " Radiology 220, 13-30 (2001).
4. A. T. Stavros, D. Thickman, C. L. Rapp, M. A. Dennis, S. H. Parker, and G. A. Sisney, " Solid breast nodules: Use of sonography to distinguish between benign and malignant lesions., " Radiology 196, 123-134 (1995).
5. K. Horsch, M. L. Giger, L. A. Venta, and C. J. Vyborny, " Computerized diagnosis of breast lesions on ultrasound., " Med. Phys. 29, 157-164 (2002).
6. Z. Huo, M. L. Giger, C. J. Vyborny, U. Bick, and P. Lu, " Analysis of speculation in the computerized classification of mammographic masses., " Med. Phys. 22, 1569-1579 (1995).
7. M. A. Kupinski and M. L. Giger, " Automated seeded lesion segmentation on digital mammograms., " IEEE Trans. Med. Imaging 17, 510-517 (1998).
8. N. Petrick, H. P. Chan, B. Sahiner, and M. A. Helvie, " Combined adaptive enhancement and region-growing segmentation of breast masses on digitized mammograms., " Med. Phys. 26, 1642-1654 (1999).
9. H. D. Li, M. Kallergi, L. P. Clarke, and V. K. Jain, " Markov random field for tumor detection in digital mammography., " IEEE Trans. Med. Imaging 14, 565-576 (1995).
10. S. Timp and N. Karssemeijer, " A new 2D segmentation method based on dynamic programming applied to computer aided detection in mammography., " Med. Phys. 31, 958-971 (2004).
11. D. Guliato, R. M. Rangayyan, W. A. Carnielli, J. A. Zuffo, and J. E. L. Desautels, " Segmentation of breast tumors in mammograms using fuzzy sets., " J. Electron. Imaging 12, 369-378 (2003).
12. H. Li, Y. Wang, K. J. R. Liu, S. B. Lo, and M. T. Freedman, " Computerized radiographic mass detection-Part 1: Lesion site selection by morphological enhancement and contextual segmentation., " IEEE Trans. Med. Imaging 20, 289-301 (2001).
13. M. Kass, A. Witkin, and D. Terzopoulos, " Snakes: Active contour models., " Int. J. Comput. Vis. 1, 321-331 (1987).
14. T. Cootes, A. Hill, C. Taylor, and J. Haslam, " The use of active shape models for locating structures in medical images., " Image Vis. Comput. 12, 355-366 (1994).
15. M. S. Atkins and B. Mackiewich, " Fully automatic segmentation of the brain in MRI., " IEEE Trans. Med. Imaging 17, 98-107 (1998).
16. A. Yezzi, S. Kichenassamy, A. Kumar, P. Olver, and A. Tannenbaum, " A geometric snake model for segmentation of medical imagery., " IEEE Trans. Med. Imaging 16, 199-209 (1997).
17. C. Xu, D. L. Pham, and J. L. Prince, " Medical image segmentation using deformable models., " in Handbook of Medical Imaging: Medical Imaging Processing and Analysis, edited by, M. Sonka, and, M. J. Fitzpatrick, (2000), vol. 2 of Proc. SPIE, pp. 129-174.
18. J. Yang, L. H. Staib, and J. S. Duncan, " Neighbor-constrained segmentation with level set based 3D deformable models., " IEEE Trans. Med. Imaging 23, 940-948 (2004).
19. F. Liu, B. Zhao, and P. K. Kijewski, " Liver segmentation for CT images using GVF snake., " Med. Phys. 32, 3699-3706 (2005).
20. G. M. Brake and N. Karssemeijer, " Segmentation of suspicious densities in digital mammograms., " Med. Phys. 28, 259-266 (2001).
21. B. Sahiner, N. Petrick, H. P. Chan, L. M. Hadjiiski, C. Paramagul, M. A. Helvie, and M. N. Gurcan, " Computer-aided characterization of mammographic masses: accuracy of mass segmentation and its effects on classification., " IEEE Trans. Med. Imaging 20, 1275-1284 (2001).
22. V. Caselles, R. Kimmel, and G. Sapiro, " Geodesic active contours., " Int. J. Comput. Vis. 22, 61-79 (1997).
23. R. Malladi, J. A. Sethian, and B. C. Vemuri, " Shape modeling with front propagation: A level set approach., " IEEE Trans. Pattern Anal. Mach. Intell. 17, 158-175 (1995).
24. S. Osher and J. A. Sethian, " Fronts propagating with curvature-dependent speed: Algorithms based on Hamilton-Jacobi formulation., " J. Comput. Phys. 79, 12-49 (1988).
25. T. F. Chan and L. A. Vese, " Active contours without edges., " IEEE Trans. Image Process. 10, 266-277 (2001).
26. J. A. Sethian, Level Set Methods and Fast Marching Methods: Evolving Interfaces in Computational Geometry, Fluid Mechanics, Computer Vision, and Materials Science (Cambridge University Press, Cambridge, 1999).
27. S. J. Osher and R. P. Fedkiw, Level Set Methods and Dynamic Implicit Surfaces (Springer, New York, 2002).
28. C. Li, C. Xu, C. Gui, and M. D. Fox, " Level set evolution without reinitialization: A new variational formulation., " In Proc. 2005 IEEE CVPR (San Diego,, 2005), pp. 1:430-436.
29. L. Rudin, S. Osher, and E. Fatemi, " Nonlinear total variation based noise removal algorithms., " J. Phys. D 60, 259-268 (1992).
30. R. Kimmel, Numerical Geometry of Images: Theory, Algorithms, and Applications (Springer, New York, 2003).
31. K. N. Chaudhury and K. R. Ramakrishnan, " Stability and convergence of the level set method in computer vision., " Pattern Recogn. Lett. 28, 884-893 (2007).
32. Y. Yu and J. A. Molloy, " Segmentation of the prostate from suprapubic ultrasound images., " Med. Phys. 31, 3474-3484 (2004).
33. Y. Yuan, M. L. Giger, K. Suzuki, H. Li, and A. R. Jamieson, " A two-stage method for lesion segmentation on digital mammograms., " in Medical Imaging: Image processing, edited by, J. M. Reinhardt, and, J. P. W. Pluim, (2006), vol. 6144 of Proc. SPIE, pp. 61443W:1-5.
34. S. A. Glantz, Primer of Biostatistics (McGraw-Hill, New York, 2002).
35. H. Li, M. L. Giger, Y. Yuan, L. Lan, K. Suzuki, A. R. Jamieson, and C. Sennett, " Comparison of computerized image analysis for digitized screen film mammograms and full field digital mammography images., " in Digital Mammography, edited by, S. M. Astley,,, M. Brady,,, C. Rose,, and, R. Zwiggelaar, (2006), vol. LNCS4046 of IWDM 2006, pp. 569-575.