Abstract
We have developed an algorithm for segmenting objects with simple closed curves, such as the heart and the lungs, that is independent of the imaging modality used (e.g., MRI, CT, echocardiography). Our method is automatic and requires as initialization a single pixel within the boundaries of the object. Existing segmentation techniques either require much more information during initialization, such as an approximation to the object's boundary, or are not robust to the types of noisy data encountered in the medical domain. By integrating region-based and physics-based modeling techniques we have devised a hybrid design that overcomes these limitations. In our experiments we demonstrate that this integration automates and significantly improves the object boundary detection results, independent of the imaging modality used.
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© 1997 Springer-Verlag Berlin Heidelberg
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Jones, T.N., Metaxas, D.N. (1997). Segmentation using deformable models with affinity-based localization. In: Troccaz, J., Grimson, E., Mösges, R. (eds) CVRMed-MRCAS'97. CVRMed MRCAS 1997 1997. Lecture Notes in Computer Science, vol 1205. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0029224
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DOI: https://doi.org/10.1007/BFb0029224
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