A brain MR image segmentation method based on Gaussian model and Markov random field

2016 ◽  
Author(s):  
Kai-Bin Liang ◽  
Yi-Hong Guan ◽  
Ya-Tao Luo
Keyword(s):  
Image Segmentation ◽  
Random Field ◽  
Markov Random Field ◽  
Gaussian Model ◽  
Segmentation Method ◽  
Mr Image ◽  
Markov Random ◽  
Mr Image Segmentation

Research on Statistic-Based Image Segmentation Method

2012 ◽  
Vol 461 ◽  
pp. 575-578 ◽  
Author(s):  
Yi Min Hou ◽  
Chun Ting Zhang ◽  
Xiao Yan Lai ◽  
Jian Ming Di
Keyword(s):  
Image Segmentation ◽  
Random Field ◽  
Markov Random Field ◽  
Optimization Algorithm ◽  
Image Noise ◽  
Segmentation Method ◽  
The Third ◽  
Markov Random ◽  
Class Segmentation ◽  
Multiple Class

The paper researched the image segmentation method based on statistic. For the multiple class segmentation, the K-means segmentation was employed in the first part. The segmentation method named OTSU is discussed in the second part of this paper. To solve the problem of the image noise, the method based on the Markov Random Field (MRF) is proposed in the third part of the paper. The ICM optimization algorithm is used in the procedure of MRF segmentation. In the experiments part, the methods are compared with each other, and the results showed that the method based on MRF are more efficient to remove the noise in the images.

Image Segmentation Method Based on Dual Feature Markov Random Field

2020 ◽  
Vol 57 (22) ◽  
pp. 221014
Author(s):  
段明义 Duan Mingyi ◽  
卢印举 Lu Yinju ◽  
苏玉 Su Yu
Keyword(s):  
Image Segmentation ◽  
Random Field ◽  
Markov Random Field ◽  
Segmentation Method ◽  
Markov Random
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