Abstract
A revised group method of data handling (GMDH)-type neural network algorithm using various kinds of neuron is applied to the medical image diagnosis of lung cancer. The optimum neural network architecture for medical image diagnosis is automatically organized using a revised GMDH-type neural network algorithm, and the regions of lung cancer are recognized and extracted accurately. In this revised GMDH-type neural network algorithm, polynomial-type and radial basis function (RBF)-type neurons are used for organizing the neural network architecture in order to fit the complexity of the nonlinear system.
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This work was presented in part at the 16th International Symposium on Artificial Life and Robotics, Oita, Japan, January 27–29, 2011
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Kondo, T., Ueno, J. Medical image diagnosis of lung cancer by a revised GMDH-type neural network using various kinds of neuron. Artif Life Robotics 16, 301–306 (2011). https://doi.org/10.1007/s10015-011-0936-6
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DOI: https://doi.org/10.1007/s10015-011-0936-6