Brain MR image segmentation based on Gaussian mixture model with spatial information

2010 ◽  
Author(s):  
Feng Zhu ◽  
Yuqing Song ◽  
Jianmei Chen
Keyword(s):  
Image Segmentation ◽  
Gaussian Mixture Model ◽  
Mixture Model ◽  
Spatial Information ◽  
Gaussian Mixture ◽  
Mr Image ◽  
Mr Image Segmentation

Adaptive scale fuzzy local Gaussian mixture model for brain MR image segmentation

2014 ◽  
Vol 134 ◽  
pp. 60-69 ◽  
Author(s):  
Zexuan Ji ◽  
Yong Xia ◽  
Quansen Sun ◽  
Qiang Chen ◽  
Dagan Feng
Keyword(s):  
Image Segmentation ◽  
Gaussian Mixture Model ◽  
Mixture Model ◽  
Gaussian Mixture ◽  
Mr Image ◽  
Mr Image Segmentation

Fuzzy Local Gaussian Mixture Model for Brain MR Image Segmentation

2012 ◽  
Vol 16 (3) ◽  
pp. 339-347 ◽  
Author(s):  
Zexuan Ji ◽  
Yong Xia ◽  
Quansen Sun ◽  
Qiang Chen ◽  
Deshen Xia ◽  
...  
Keyword(s):  
Image Segmentation ◽  
Gaussian Mixture Model ◽  
Mixture Model ◽  
Gaussian Mixture ◽  
Mr Image ◽  
Mr Image Segmentation

Traffic Image Segmentation Based on Gaussian Mixture Model with Spatial Information and Sampling

2013 ◽  
Vol 380-384 ◽  
pp. 3702-3705
Author(s):  
Xiao Na Zhang ◽  
Ming Yao ◽  
Feng Zhu ◽  
Jie Ni
Keyword(s):  
Image Segmentation ◽  
Gaussian Mixture Model ◽  
Mixture Model ◽  
Spatial Information ◽  
Gaussian Mixture ◽  
Sampling Theorem ◽  
Information Function ◽  
Cluster Number ◽  
Minimum Sample ◽  
Image Pixels

The application of classical gaussian mixture model to image segmentation has highly computer complexiton and have not taking into account spatial information except intensity values. A image segmentation based on Gaussian mixture model with sampling and spatially information is proposed in order to solve this problem. First, a spatial information function is defined as the neighbour information weighted class probabilities of very pixels; Secondly, the sampling theorem is given in this paper,and the size of the minimum sample has been derived according to the smallest cluster and cluster number; Finally, image pixels are sampled based on the size of the minimum sample to estimate the parameter of model , which are classifed to different clusters according to bayesian rules. The experimental results show the effectiveness of the algorithm.

A spatially constrained asymmetric Gaussian mixture model for image segmentation

2021 ◽  
Author(s):  
Yunjie Chen ◽  
Ning Cheng ◽  
Mao Cai ◽  
Chunzheng Cao ◽  
Jianwei Yang ◽  
...  
Keyword(s):  
Image Segmentation ◽  
Gaussian Mixture Model ◽  
Mixture Model ◽  
Gaussian Mixture
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