Authors
Tadashi Kondo, Junji Ueno, Shoichiro Takao
Corresponding Author
Tadashi Kondo
Available Online 1 June 2016.
DOI
https://doi.org/10.2991/jrnal.2016.3.1.5
Keywords
Deep neural networks, GMDH, Medical image recognition, Evolutionary computation,
X-ray CT image.
Abstract
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.
Copyright
© 2013, the Authors. Published by ALife Robotics Corp. Ltd.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).