Application of radial basis function artificial neural network in image diagnosis of cervical cells
Miao He · Zhongguo Yike Daxue xuebao · 2006
Objective: To investigate the possibility of applying artificial neural network based on radial basis function(RBF) to image recognition of cervical cells.Methods:According to 15 morphologic parameters and 12 chromatic parameters of cervical cells,700 cervical cells were classified as normal cells,low-grade squamous intraepithelial lesion(LSIL) cells,high-grade squamous intraepithelial lesion(HSIL) cells,and cervical cancer cells.STATISTICA 7.0 was used to establish and train the neural network model,and VC++.NET was used to call the model.Results:The goodness of fit of the neural network model in training set was 97.3%,and the classification accuracy in testing set was 95.4%.In testing set,the recognition rate was 96% in normal cells,94% in LSIL cells,100% in HSIL cells,and 88% in cervical cancer cells.The sensitivity order of input parameters in the RBF artificial neural network was approximately consistent with that of characteristics of cell pathology.Conclusion:Cervical cancer cells,especially HSIL cells,can be well recognized by RBF artificial neural networks.RBF neural network can be widely applied in computer aided diagnosis.