Medical Image Segmentation Based on a Hybrid Region-Based Active Contour Model
2014 ◽
Vol 2014
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pp. 1-10
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Keyword(s):
A novel hybrid region-based active contour model is presented to segment medical images with intensity inhomogeneity. The energy functional for the proposed model consists of three weighted terms: global term, local term, and regularization term. The total energy is incorporated into a level set formulation with a level set regularization term, from which a curve evolution equation is derived for energy minimization. Experiments on some synthetic and real images demonstrate that our model is more efficient compared with the localizing region-based active contours (LRBAC) method, proposed by Lankton, and more robust compared with the Chan-Vese (C-V) active contour model.
2020 ◽
Vol 2020
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pp. 1-14
2014 ◽
Vol 2014
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pp. 1-13
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2012 ◽
Vol 532-533
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pp. 892-896
Keyword(s):
2014 ◽
Vol 6
(2)
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pp. 33-49
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2016 ◽
Vol 2016
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pp. 1-10
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Keyword(s):
2010 ◽
Vol 121-122
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pp. 222-227
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Keyword(s):
2013 ◽
Vol 2013
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pp. 1-14
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2015 ◽
Vol 2015
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pp. 1-19
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