Ultrasound-based tissue characterization and classification of fatty liver disease: A screening and diagnostic paradigm

作者：

Highlights：

• We review the modalities that detect Fatty Liver Disease (FLD).

• We review the ultrasound-based Computer Aided Diagnostic techniques for FLD detection.

• We conclude that there is need for more clinical trials to evaluate these techniques.

摘要

•We review the modalities that detect Fatty Liver Disease (FLD).•We review the ultrasound-based Computer Aided Diagnostic techniques for FLD detection.•We conclude that there is need for more clinical trials to evaluate these techniques.

论文关键词：ALT,Alanine Aminotransferase,AHP,Analytic Hierarchy Process,ASM,Angular Second Moment,ANN,Artificial Neural Network,CBR,Case-Based Reasoning,CART,Classification And Regression Tree,CWT,Continuous Wavelet Transforms,CAD,Computer-Aided Diagnosis,CT,Computed Tomography,DT,Decision Trees,DWT,Discrete Wavelet Transform,FFS,Far-Field Slope,FLD,Fatty Liver Disease,FDTA,Fractal Dimension Texture Analysis,FSC,Fuzzy Sugeno Classifier,GLCM,Gray Level Co-occurrence Matrix,GLDS,Gray Level Difference Statistics,RUNL,Gray Level Run Length Statistics,HOS,Higher Order Spectra,k-NN,k-Nearest Neighbor Classifier,LBP,Local Binary Pattern,MRI,Magnetic Resonance Imaging,MGL,Mean Gray Level,NAFLD,Non-Alcoholic Fatty Liver Disease,RBF,Radial Basis Function,SGLDM,Spatial Gray Level Dependence Matrices,SVM,Support Vector Machine,US,Ultrasound,WPD,Wavelet Packet Decomposition,Computer Aided Diagnosis,Ultrasound,Fatty Liver Disease,Review,Non Alcoholic Steatohepatitis

论文评审过程：Received 21 May 2014, Revised 26 October 2014, Accepted 17 November 2014, Available online 1 December 2014.

论文官网地址：https://doi.org/10.1016/j.knosys.2014.11.021