Abstract
In this paper we develop a multi-object prior shape model for use in curve evolution-based image segmentation. Our prior shape model is constructed from a family of shape distributions (cumulative distribution functions) of features related to the shape. Shape distribution-based object representations possess several desired properties, such as robustness, invariance, and good discriminative and generalizing properties. Further, our prior can capture information about the interaction between multiple objects. We incorporate this prior in a curve evolution formulation for shape estimation. We apply this methodology to problems in medical image segmentation.
This work was partially supported by AFOSR grant F49620-03-1-0257, National Institutes of Health under Grant NINDS 1 R01 NS34189, Engineering research centers program of the NSF under award EEC-9986821. The MR brain data sets and their manual segmentations were provided by the Center for Morphometric Analysis at Massachusetts General Hospital and are available at http://www.cma.mgh.harvard.edu/ibsr/.
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Litvin, A., Karl, W.C. (2005). Coupled Shape Distribution-Based Segmentation of Multiple Objects. In: Christensen, G.E., Sonka, M. (eds) Information Processing in Medical Imaging. IPMI 2005. Lecture Notes in Computer Science, vol 3565. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11505730_29
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DOI: https://doi.org/10.1007/11505730_29
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