Medical image recognition by using logistic GMDH-type neural networks

In this study, the logistic GMDH-type neural networks are applied to the medical image recognition. This neural network algorithm is based on the conventional GMDH-type neural networks that can automatically organize neural network architecture by using the heuristic self-organization method. In the logistic GMDH-type neural networks, a lot of complex nonlinear combinations of the input variables fitting the complexity of the nonlinear system are generated and only useful combinations of the input variables are selected for organizing the neural network architecture. Therefore, the neural networks organized by the logistic GMDH-type neural networks have good generalization ability even if the characteristic of the nonlinear system is very complex. In this study, the logistic GMDH-type neural networks are applied to the medical image recognition and it is shown that the logistic GMDH-type neural networks are accurate and useful method for the medical image recognition.