Computerized Detection of Liver Cirrhosis Using Wave Pattern of Spleen in Abdominal CT Images

2004 ◽  
pp. 589-594
Author(s):  
Won Seong ◽  
June-Sik Cho ◽  
Seung-Moo Noh ◽  
Jong-Won Park
Keyword(s):  
Liver Cirrhosis ◽  
Wave Pattern ◽  
Ct Images ◽  
Abdominal Ct

An Automatic Grading Method of Liver Cirrhosis from Abdominal CT Images

2021 ◽  
Author(s):  
Xianru Zhang ◽  
Yujie Nie ◽  
Xu Qiao ◽  
Kai Li ◽  
Wei Chen ◽  
...  
Keyword(s):  
Liver Cirrhosis ◽  
Ct Images ◽  
Abdominal Ct ◽  
Automatic Grading

scholarly journals Liver tumour classification using average correction higher order local autocorrelation coefficient and legendre moments

2018 ◽  
Vol 7 (2.6) ◽  
pp. 306
Author(s):  
Aravinda H.L ◽  
M.V Sudhamani
Keyword(s):  
Texture Feature ◽  
Region Growing ◽  
Ct Images ◽  
Higher Order ◽  
Liver Carcinoma ◽  
Tumor Segmentation ◽  
Abdominal Ct ◽  
Simple Linear Iterative Clustering ◽  
Classification Of Tumors ◽  
Legendre Moments

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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