基于C-V模型的医学图像分割方法

Abstract

Abstract:

This paper focuses on two different GAC models:Li Chunming model based on gradient information and C-V model based on region information.In light of the drawbacks and advantages of these two models,we introduce penalty-function to C-V mode,and propose a C-V model without re-initialization.A comparison between the two models shows that the proposed model incorporates the segmentation speed of Li Chunming model and the segmentation performance of C-V model.

Key words: image segmentation;active contour model;level set

CLC Number:

TP391.41

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WEI Ming-Xiang, CHEN Jun. Medical Image Segmentation Based on C-V model[J]., 2012, 25(5): 101-.

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URL: https://journal.xidian.edu.cn/dzkj/EN/

https://journal.xidian.edu.cn/dzkj/EN/Y2012/V25/I5/101

References

［1］KASS M,WITKIN A.TERZOPOULOS D.Snakes:active contour models［J］.International Journal of Computer Vision,1987,1(4):321-331.

［2］CASELLES V,CATTE T,COLL T,et al.A geometric model for active contours in image processing［J］.Numeric Math,1993,66(1):1-31.

［3］LI Chunming,XU Chenyang,GUI Changfeng,et al.Level set evolution without re-initialization:a new variational formulation［C］.Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (C-VPR05),2005,1:430-436.

［4］CHAN L V.Active contours model without edges［J］.IEEE Transactions on Image Processing,2001,10(2):266-277.

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Medical Image Segmentation Based on C-V model

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