Abstract
In this study, we propose a revised radial basis function (RBF) neural network algorithm and apply this algorithm to computer-aided diagnosis (CAD) of the liver. First, the revised RBF neural network algorithm is applied to recognition of the liver regions, and the recognition results are compared with those obtained using the conventional RBF neural network and the conventional multilayered neural network trained using the back-propagation algorithm. It is shown that the revised RBF neural network is accurate, and is a useful method because the parameters are automatically determined. Then, the revised RBF neural network is applied to CAD of the liver cancer called hepatocellular carcinoma (HCC).
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This work was presented in part at the 14th International Symposium on Artificial Life and Robotics, Oita, Japan, February 5–7, 2009
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Nakagawa, M., Kondo, T., Kudo, T. et al. Three-dimensional medical image recognition of cancer of the liver by a revised radial basis function (RBF) neural network algorithm. Artif Life Robotics 14, 118–122 (2009). https://doi.org/10.1007/s10015-009-0640-y
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DOI: https://doi.org/10.1007/s10015-009-0640-y