Abstract
This paper presents a novel methodology to obtain the breast skin line in mammographic images. The breast edge provides important information of the breast shape and deformation which is posteriorly used by other processing techniques, typically mammographic image registration and abnormality detection. The proposed methodology is based on applying edge detection algorithms and scale space concepts. The proposed method is a particular implementation (application focused) of a growing active contour with common considerations. Quantitative and qualitative evaluation is provided to show the validity of the approach.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
American Cancer Society: Breast cancer: facts and figures. 2003-04. ACS (2003)
Sallam, M., Bowyer, K.: Registration and difference analysis of corresponding mammogram images. Medical Image Analysis 3(2), 103–118 (1999)
Yin, F., Giger, M., Doi, K., Vyborny, C., Schmidt, R.: Computerized detection of masses in digital mammograms: automated alignment of breast images and its effect on bilateral-subtraction technique. Med. Phys. 21(3), 445–452 (1994)
Mendez, A., Tahoces, P., Lado, M., Souto, M., Correa, J., Vidal, J.: Automatic detection of breast border and nipple in digital mammograms. Comput. Methods Programs Biomed. 49(3), 253–262 (1998)
Wirth, M., Nikitenko, D., Lyon, J.: Segmentation of the Breast Region in Mammograms using a Rule-Based Fuzzy Reasoning Algorithm. ICGST International Journal on Graphics, Vision and Image Processing 5(2) (2005)
Chandrasekhar, R., Attikiouzel, Y.: Gross segmentation of mammograms using a polynomial model. Proc. Eng. Med. and Biol. Soc. 3, 1056–1058 (1996)
Raba, D., Oliver, A., Martí, J., Peracaula, M., Espunya, J.: Breast segmentation with pectoral muscle suppression on digital mammograms. In: Marques, J.S., Pérez de la Blanca, N., Pina, P. (eds.) IbPRIA 2005. LNCS, vol. 3523, pp. 471–478. Springer, Heidelberg (2005)
Pan, X., Brady, M., Highnam, R., Declerck, J.: The use of multi-scale monogenic signal on structure orientation identification and segmentation. In: Astley, S.M., Brady, M., Rose, C., Zwiggelaar, R. (eds.) IWDM 2006. LNCS, vol. 4046, pp. 601–608. Springer, Heidelberg (2006)
Lindeberg, T.: Edge detection and ridge detection with automatic scale selection. International Journal of Computer Vision 30(2), 117–154 (1998)
Deschênes, J., Ziou, D.: Detection of line junctions and line terminations using curvilinear features. Pattern Recognition Letters 21, 637–649 (2000)
Suckling, J., Parker, J., Dance, D., Astley, S., Hutt, I., Boggis, C., Ricketts, I., Stamatakis, E., Cerneaz, N., Kok, S., Taylor, P., Betal, D., Savage, J.: The Mammographic Image Analysis Society digital mammogram database. In: International Workshop on Digital Mammography, pp. 211–221 (1994)
Heath, M., Bowyer, K., Kopans, D., Moore, R., Kegelmeyer, P.: The digital database for screening mammography. In: International Workshop on Digital Mammography (2000)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer Berlin Heidelberg
About this paper
Cite this paper
Martí, R., Oliver, A., Raba, D., Freixenet, J. (2007). Breast Skin-Line Segmentation Using Contour Growing. In: Martí, J., Benedí, J.M., Mendonça, A.M., Serrat, J. (eds) Pattern Recognition and Image Analysis. IbPRIA 2007. Lecture Notes in Computer Science, vol 4478. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72849-8_71
Download citation
DOI: https://doi.org/10.1007/978-3-540-72849-8_71
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72848-1
Online ISBN: 978-3-540-72849-8
eBook Packages: Computer ScienceComputer Science (R0)