Computer Science ›› 2017, Vol. 44 ›› Issue (10): 45-50.doi: 10.11896/j.issn.1002-137X.2017.10.008

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Cirrhosis Recognition Based on Improved LBP Algorithm and Extreme Learning Machine

LEI Yi-ming, ZHAO Xi-mei, WANG Guo-dong and YU Ke-xin   

  • Online:2018-12-01 Published:2018-12-01

Abstract: Computer aided diagnosis of cirrhoisis has great meaning for the early treatment and diagnosis of liver di-sease.For the issues that edge blurring and nonuniform of echo in cirrhosis lesion area and influence of scale factor in B-mode ultrasound images,we proposed an improved LBP algorithm and extracted the corresponding SLBP feature which depicts the lesion area of cirrhosis more precisely than traditional texture features.Through the combination of SLBP and two-dimensional Gabor transform,we solved the difficulties above.Due to the long training time of conventional machine learning methods,we adopted extreme learning machine based method and firstly applied it in cirrhosis recognition.Experimental results show that classification accuracy on test set reaches 95.4%,and time efficiency has further improved compared with traditional method.The comparison between the proposed method and conventional methods,via ROC(Receiver Operating Characteristic) curve,demonstrates that the proposed method possesses the advantages both in accuracy and generalization performance.The proposed method will be helpful for clinical diagnosis of cirrhosis.

Key words: Cirrhosis,Extreme learning machine,Improved LBP algorithm,SLBP feature,Gabor transform,ROC curve

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