Medical Image Analysis of Brain X-ray CT Images By Deep GMDH-Type Neural Network

DOI

10.2991/jrnal.2016.3.1.5How to use a DOI?

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 Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - Tadashi Kondo
AU  - Junji Ueno
AU  - Shoichiro Takao
PY  - 2016
DA  - 2016/06/01
TI  - Medical Image Analysis of Brain X-ray CT Images By Deep GMDH-Type Neural Network
JO  - Journal of Robotics, Networking and Artificial Life
SP  - 17
EP  - 23
VL  - 3
IS  - 1
SN  - 2352-6386
UR  - https://doi.org/10.2991/jrnal.2016.3.1.5
DO  - 10.2991/jrnal.2016.3.1.5
ID  - Kondo2016
ER  -