An Effective Evaluation Method of Non-Rigid Registration of Multiphase Abdominal CT Images

Author(s):  
Ji Li ◽  
Zhi-liang Zhu ◽  
Li-li Feng ◽  
Hui-yan Jiang
2021 ◽  
Vol 70 ◽  
pp. 102976
Author(s):  
Shao-di Yang ◽  
Yu-qian Zhao ◽  
Zhen Yang ◽  
Yan-jin Wang ◽  
Fan Zhang ◽  
...  

2021 ◽  
Author(s):  
Xianru Zhang ◽  
Yujie Nie ◽  
Xu Qiao ◽  
Kai Li ◽  
Wei Chen ◽  
...  

2018 ◽  
Vol 7 (2.6) ◽  
pp. 306
Author(s):  
Aravinda H.L ◽  
M.V Sudhamani

The major reasons for liver carcinoma are cirrhosis and hepatitis.  In order to  identify carcinoma in the liver abdominal CT images are used. From abdominal CT images, segmentation of liver portion using adaptive region growing, tumor segmentation from extracted liver using Simple Linear Iterative Clustering is already implemented. In this paper, classification of tumors as benign or malignant is accomplished using Rough-set classifier based on texture feature extracted using Average Correction Higher Order Local Autocorrelation Coefficients and Legendre moments. Classification accuracy achieved in proposed scheme is 90%. The results obtained are promising and have been compared with existing methods.


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