Computer Science ›› 2016, Vol. 43 ›› Issue (4): 303-307.doi: 10.11896/j.issn.1002-137X.2016.04.062

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Medical Image Segmentation Based on Region-based Hybrid Active Contour Model

LIN Xi-lan, CHEN Xiu-hong and XIAO Lin-yun   

  • Online:2018-12-01 Published:2018-12-01

Abstract: In view of the phenomenon that the calculation of variational level set algorithm is much larger and the speed is too low in the process of image segmentation,this paper proposed a new region-based hybrid nonconvex regularization active contour model based on some region-based active contour models.This model constructs a new energy functional which incorporates the LBF model having the property of local clustering of an image and geodesic active contour mo-del.By adding a nonconvex regularization term,they fasten the convergence speed of the contour curve,and can well pre-serve the shape of the region and protect the edge from oversmoothing.Thus,the minimum of the energy functional will be obtained by the typical finite difference method.Results of the simulation experiment on synthetic and medical images show that the proposed algorithm has quite fast convergence rate,accurate segmentation results and better robustness.

Key words: LBF model,Geodesic model,Hybrid model,Nonconvex regularization,Medical image

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