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A revised group method of data handling (GMDH)-type neural network algorithm for medical image recognition is proposed and is applied to 3-dimensional medical image analysis of the heart. The revised GMDH-type neural network algorithm has a feedback loop and can identify the characteristics of the medical images accurately using feedback loop calculations. In this algorithm, the polynomial type and...
The feedback group method of data handling (GMDH)-type neural network algorithm proposed in this paper is applied to 3-dimensional medical image recognition of the brain. The neural network architecture fitting the complexity of the medical images is automatically organized so as to minimize the prediction error criterion defined as Akaikepsilas information criterion (AIC) or prediction sum of squares...
In this study, a feedback group method of data handling (GMDH)-type neural network algorithm using prediction error criterion for self-organization is proposed. In this algorithm, the optimum neural network architecture is automatically selected from three types of neural network architectures such as the sigmoid function type neural network, the radial basis function (RBF) type neural network and...
A radial basis function (RBF) group method of data handling (GMDH)-type neural network algorithm proposed in this paper is applied to the medical image recognition of abdominal X-ray CT images. The optimum neural network architecture for the medical image recognition is automatically organized using RBF GMDH-type neural network algorithm and the regions of abdominal organs such as the liver, stomach...
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