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Feedback GMDH-type neural network algorithm and its application to medical image analysis of cancer of the liver

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Abstract

A revised group method of data handling (GMDH)-type neural network algorithm for medical image recognition is proposed, and is applied to medical image analysis of cancer of the liver. 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 radial basis function (RBF)-type neurons are used for organizing the neural network architecture. The optimum neural network architecture fitting the complexity of the medical images is automatically organized so as to minimize the prediction error criterion, defined as the prediction sum of squares (PSS).

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References

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Authors and Affiliations

  1. School of Health Sciences, University of Tokushima, 3-18-15 Kuramoto-cho, Tokushima, 770-8509, Japan

    Tadashi Kondo, Shoichiro Takao & Junji Ueno

  2. Graduate School of Media Design, Keio University, Yokohama, Japan

    Chihiro Kondo

Authors
  1. Tadashi Kondo
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  2. Chihiro Kondo
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  3. Shoichiro Takao
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  4. Junji Ueno
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Corresponding author

Correspondence to Tadashi Kondo.

Additional information

This work was presented in part at the 15th International Symposium on Artificial Life and Robotics, Oita, Japan, February 4–6, 2010

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Kondo, T., Kondo, C., Takao, S. et al. Feedback GMDH-type neural network algorithm and its application to medical image analysis of cancer of the liver. Artif Life Robotics 15, 264–269 (2010). https://doi.org/10.1007/s10015-010-0805-8

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  • DOI: https://doi.org/10.1007/s10015-010-0805-8

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