Volume 3, Issue 1, June 2016, Pages 17 - 23
Medical Image Analysis of Brain X-ray CT Images By Deep GMDH-Type Neural Network
Tadashi Kondo, Junji Ueno, Shoichiro Takao
Available Online 1 June 2016.
- 10.2991/jrnal.2016.3.1.5How to use a DOI?
- Deep neural networks, GMDH, Medical image recognition, Evolutionary computation, X-ray CT image.
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.
- © 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/).
Cite this article
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 -