Unsupervised Abdomen CT Image Segmentation using Variable Weight MRF in Spatial and Wavelet Domain

被引:0
|
作者
Ma, Zhiyuan [1 ]
Jiang, Huiyan [1 ]
Yang, Benqiang [2 ]
Zhang, Libo [2 ]
机构
[1] Northeastern Univ, Software Coll, Shenyang, Liaoning, Peoples R China
[2] Peoples Liberat Army Gen Hosp, Dept Radiol, Shenyang, Liaoning, Peoples R China
关键词
Image segmentation; Abdomen CT imag; Markov Random Field; Simulated Annealing; MAP; ICM; RELAXATION ALGORITHMS; MODELS;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Aiming at the segmentation of liver image with fuzzy edge, a new algorithm based on Markov Random Field in spatial and wavelet domains is proposed. Firstly, a lifting wavelet transform is adopted to represent an original image in different resolutions; Secondly, attain the low frequency sub-image and execute an initial segmentation and a multi-level segmentation; Lastly, the spatial domain transform is applied on the segmentation result of the wavelet domain to revise the segmentation results and to get an accurate outcome. The algorithms of the initial and multi-level segmentation in wavelet domain are K-means improved by SAPSO and MAP/ICM. Experimental results show that the proposed algorithm has a good robustness.
引用
收藏
页码:915 / 920
页数:6
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