MEDICAL IMAGES SEGMENTATION USING ACTIVE CONTOURS DRIVEN BY GLOBAL AND LOCAL IMAGE FITTING ENERGY
2012 ◽
Vol 12
(02)
◽
pp. 1250015
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Keyword(s):
In this paper, we propose a global and local Chan-Vese model which utilizes both global image information and local image information for image segmentation. We define an energy functional with a global term, which incorporates global image information to improve the robustness of the proposed method, and a local term which is dominant near the object boundaries. The regularization term is added to the energy functional to avoid the time-consuming re-initialization. The comparisons with the C–V model, LBF model and LGIF model show that our model can segment images with intensity inhomogeneity in less iteration steps and take less time.
2012 ◽
Vol 532-533
◽
pp. 1583-1587
2012 ◽
Vol 616-618
◽
pp. 2223-2228
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Keyword(s):
2019 ◽
Vol 15
(1)
◽
pp. 247
2014 ◽
Vol 2014
◽
pp. 1-13
◽
2014 ◽
Vol 513-517
◽
pp. 3463-3467