An integrated method for breast mass segmentation in digitized mammograms

Breast mass segmentation is often required as a significant step for monitoring and quantifying breast cancer. In this paper, we present an efficient approach for breast mass segmentation. The proposed method is composed of two steps. Firstly, the marker controlled watershed algorithm is applied to mammograms as an initial segmentation. Then, the contour line obtained by watershed is regarded as the initial curve and a level set evolution without re-initialization is utilized for the further segmentation. This integrated approach yields a robust and precise segmentation. The effectiveness of the proposed approach is validated using extensive experiments on the MIAS and DDSM databases.

[1]  Chunming Li,et al.  Level set evolution without re-initialization: a new variational formulation , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[2]  Xie Yuan-dan,et al.  Survey on Image Segmentation , 2002 .

[3]  Luc Vincent,et al.  Watersheds in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[4]  J. MacQueen Some methods for classification and analysis of multivariate observations , 1967 .

[5]  Ping Wang,et al.  A Modified FCM Algorithm for MRI Brain Image Segmentation , 2008 .

[6]  Xiao Han,et al.  A Topology Preserving Level Set Method for Geometric Deformable Models , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[7]  Arnau Oliver,et al.  Automatic Mass Segmentation in Mammographic Images , 2008 .

[8]  H P Chan,et al.  Combined adaptive enhancement and region-growing segmentation of breast masses on digitized mammograms. , 1999, Medical physics.

[9]  KomGuillaume,et al.  Automated detection of masses in mammograms by local adaptive thresholding , 2007 .

[10]  N. Karssemeijer,et al.  A new 2D segmentation method based on dynamic programming applied to computer aided detection in mammography. , 2004, Medical physics.

[11]  A. Malagelada Automatic mass segmentation in mammographic images , 2007 .

[12]  Aize Cao,et al.  Robust information clustering incorporating spatial information for breast mass detection in digitized mammograms , 2008, Comput. Vis. Image Underst..

[13]  S. Lai,et al.  On techniques for detecting circumscribed masses in mammograms. , 1989, IEEE transactions on medical imaging.

[14]  M. Hanmandlu,et al.  A comparison of two methods for the segmentation of masses in the digital mammograms , 2010, Comput. Medical Imaging Graph..

[15]  Ian W. Ricketts,et al.  The Mammographic Image Analysis Society digital mammogram database , 1994 .

[16]  Maryellen L. Giger,et al.  Automated seeded lesion segmentation on digital mammograms , 1998, IEEE Transactions on Medical Imaging.

[17]  Ron Kikinis,et al.  Improved watershed transform for medical image segmentation using prior information , 2004, IEEE Transactions on Medical Imaging.