A Segmentation Method Based on Dynamic Programming for Breast Mass in MRI Images

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The tumor segmentation in Breast MRI image is difficult due to the complicated galactophore structure. The work in this paper attempts to accurately segment the abnormal breast mass in MRI(Magnetic resonance imaging) Images. The ROI (Region of Interest) is segmented using a novel DP (Dynamic Programming) based optimal edge detection technique. DP is an optimal approach in multistage decision-making. The method presented in this paper processes the object image to get the minimum cumulative cost matrix combining with LUM nonlinear enhancement filter, Gaussian preprocessor, non-maximum suppression and double-threshold filtering, and then trace the whole optimal edge. The experimental results show that this method is robust and efficient on image edge detection and can segment the breast tumor area more accurately.
Publisher
Springer Verlag (Germany)
Issue Date
2008-01
Citation

Lecture Notes in Computer Science, Vol.4901, pp.307–313

ISSN
0302-9743
DOI
10.1007/978-3-540-77413-6_39
URI
http://hdl.handle.net/10203/9733
Appears in Collection
EE-Journal Papers(저널논문)

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