Boundary Segmentation of Microcalcification using Parametric Active Contours
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 32797
Boundary Segmentation of Microcalcification using Parametric Active Contours

Authors: Abdul Kadir Jumaat, Siti Salmah Yasiran, Wan Eny Zarina Wan Abd Rahman, Aminah Abdul Malek

Abstract:

A mammography image is composed of low contrast area where the breast tissues and the breast abnormalities such as microcalcification can hardly be differentiated by the medical practitioner. This paper presents the application of active contour models (Snakes) for the segmentation of microcalcification in mammography images. Comparison on the microcalcifiation areas segmented by the Balloon Snake, Gradient Vector Flow (GVF) Snake, and Distance Snake is done against the true value of the microcalcification area. The true area value is the average microcalcification area in the original mammography image traced by the expert radiologists. From fifty images tested, the result obtained shows that the accuracy of the Balloon Snake, GVF Snake, and Distance Snake in segmenting boundaries of microcalcification are 96.01%, 95.74%, and 95.70% accuracy respectively. This implies that the Balloon Snake is a better segmentation method to locate the exact boundary of a microcalcification region.

Keywords: Balloon Snake, GVF Snake, Distance Snake, Mammogram, Microcalcifications, Segmentation

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1333768

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1681

References:


[1] Pride Foundation (2012). Available: http://pride.org.my
[2] Tabar, L.; Vitak, B.; Chen, H-HT.; Yen, M-F.; Duffy, S. W.; and Smith, R. A. (2001). Beyond Randomized Trials: Organized Mammographic Screening Substantially Reduces Breast Carcinoma Mortality. Cancer 91:1724 -1731.
[3] About.com.(2012).Available: http://breastcancer.about. com/od/mammo grams/p/calcifications.htm
[4] Tabrizi, J.H. (2003), Using Active Contour for Segmentation of Middle Ear Images. McGill University, Qubee.
[5] McInerney, T., and Terzopoulos, D. (1995). A Dynamic Finite Element Surface Model for Segmentation and Tracking in Multidimensional Medical Images with Applications to Cardiac 4D Image Analysis. Computerized Medical Imaging and Graphics 19(1):69-83.
[6] Xu,C.,&Prince,J.L. (1997), "Gradient Vector Flow: A New External Force for Snakes", Proc. IEE Conf. on Computer Vision. 66-71, The John Hopkins University, Baltimore
[7] Kass M, Witkin A & Terzopoulos D (1986), "Snakes: Active Contour Models", International Journal of Computer Vision, 3, 321-331.
[8] Cohen, L., and Cohen, I. (1993). Finite-element Methods for Active Contour Models and Balloons for 2D and 3D Images. IEEE Transactions on Pattern Analysis and Machine Intelligence 15(11): 1131-1146.
[9] Sandberg.K.(2001). Visualizing Calculus: The Use of the Gradient in Image Processing. University of Colorado, Boulder
[10] Cohen,L.D. (1991). On Active Contour Models and Balloons, Computer Vision, Graphics, and Image Processing: Image Understanding. 211- 218
[11] S. Nirmala Devi and N. Kumaravel, (2008) "Comparison of active contour models for image segmentation in X-ray coronary angiogram images," Journal of medical engineering & technology, vol. 32, pp. 408-418, 2008.
[12] J. Hatamzadeh-Tabrizi and W. R. J. Funnell, (2002)."Comparison of gradient, gradient vector flow and pressure force for image segmentation using active contours," pp. 1-4..
[13] F. Liu, et al., "Liver segmentation for CT images using GVF snake," (2005). Medical Physics, vol. 32, p. 3699, 2005.
[14] A. K. Jumaat, et al., (2010) "Comparison of Balloon Snake and GVF Snake in Segmenting Masses from Breast Ultrasound Images," 2010, pp. 505-509.
[15] A. K. Jumaat, et al., (2010) "Segmentation of Masses from Breast Ultrasound Images using Parametric Active Contour Algorithm," Procedia-Social and Behavioral Sciences, vol. 8, pp. 640-647, 2010.
[16] S. S. Yasiran, et al., "Comparison between GVF snake and ED snake in segmenting microcalcifications," 2011, pp. 597-601.
[17] S. S. Yasiran, "Segmenting Microcalcifiations using Enhanced Distance Active Contour (EDAC)," MSc, Mathematics, Universiti Teknologi Mara (UiTM), Malaysia., Shah Alam, 2010.
[18] A. K. Jumaat, et al., (2011) "Segmentation and Characterization Masses in Breast Ultrasound Images Using Active Contour". 2011 IEEE International Conference on Signal and Image Processing Applications (ICSIPA2011), 16-18 November 2011.