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

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 4901))

Abstract

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.

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© 2007 Springer-Verlag Berlin Heidelberg

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Liu, J., Ma, W., Lee, SY. (2007). A Segmentation Method Based on Dynamic Programming for Breast Mass in MRI Images. In: Zhang, D. (eds) Medical Biometrics. ICMB 2008. Lecture Notes in Computer Science, vol 4901. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77413-6_39

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  • DOI: https://doi.org/10.1007/978-3-540-77413-6_39

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-77410-5

  • Online ISBN: 978-3-540-77413-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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