• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

Adaptive Active Contour Model: a Localized Mutual Information Approach for Medical Image Segmentation


Abstract

Troubles are often met when traditional active contours extract boundaries of medical images with inhomogeneous bias and various noises. Focusing on such a circumstance, a localized mutual information active contour model is discussed in the paper. By defining neighborhood of each point on the level set, mutual information is introduced to describe the relationship between the zero level set and image field. A driving energy term is then generated by integrating all the information. In addition, an expanding energy and internal energy are designed to regularize the driving energy. Contrary to piecewise constant model, new model has a better command of driving the contours without initialization


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Cite this article

[IEEE Style]
S. Dai, S. Zhan, N. Song, "Adaptive Active Contour Model: a Localized Mutual Information Approach for Medical Image Segmentation," KSII Transactions on Internet and Information Systems, vol. 9, no. 5, pp. 1840-1855, 2015. DOI: 10.3837/tiis.2015.05.016.

[ACM Style]
Shuanglu Dai, Shu Zhan, and Ning Song. 2015. Adaptive Active Contour Model: a Localized Mutual Information Approach for Medical Image Segmentation. KSII Transactions on Internet and Information Systems, 9, 5, (2015), 1840-1855. DOI: 10.3837/tiis.2015.05.016.

[BibTeX Style]
@article{tiis:20796, title="Adaptive Active Contour Model: a Localized Mutual Information Approach for Medical Image Segmentation", author="Shuanglu Dai and Shu Zhan and Ning Song and ", journal="KSII Transactions on Internet and Information Systems", DOI={10.3837/tiis.2015.05.016}, volume={9}, number={5}, year="2015", month={May}, pages={1840-1855}}