ID | 112962 |
Author |
Kondo, Tadashi
Tokushima University
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Ueno, Junji
Tokushima University
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Keywords | Deep neural networks
GMDH
Medical image recognition
Evolutionary computation
X-ray CT image
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Content Type |
Journal Article
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Description | The deep Group Method of Data Handling (GMDH)-type neural network is applied to the medical image analysis of brain X-ray CT image. In this algorithm, the deep neural network architectures which have many hidden layers and fit the complexity of the nonlinear systems, are automatically organized using the heuristic self-organization method so as to minimize the prediction error criterion defined as Akaike’s Information Criterion (AIC) or Prediction Sum of Squares (PSS). The learning algorithm is the principal component-regression analysis and the accurate and stable predicted values are obtained. The recognition results show that the deep GMDH-type neural network algorithm is useful for the medical image analysis of brain X-ray CT images.
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Journal Title |
Journal of Robotics, Networking and Artificial Life
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ISSN | 23526386
24059021
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Publisher | Atlantis Press
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Volume | 3
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Issue | 1
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Start Page | 17
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End Page | 23
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Published Date | 2016-05-31
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Rights | © The authors. This article is distributed under the terms of the Creative Commons Attribution License 4.0, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited. See for details: https://creativecommons.org/licenses/by-nc/4.0/
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language |
eng
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TextVersion |
Publisher
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departments |
Medical Sciences
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