Image processing with liver mri convolutional neural network

Authors

  • V. M. Sineglazov National Aviation University
  • V. P. Hotsyanivskyy National Aviation University

DOI:

https://doi.org/10.18372/1990-5548.50.11384

Keywords:

Automation deep learning, image processing, medicine

Abstract

The methods of learning machine learning models to analyze magnetic resonance imagingimages and identify them on the disease

Author Biographies

V. M. Sineglazov, National Aviation University

Doctor of Engineering Science. Professor.Educational and Scientific Institute of Information and Diagnostic Systems, Aviation Computer-Integrated Complexes Department

V. P. Hotsyanivskyy, National Aviation University

Student. Educational and Scientific Institute of Information and Diagnostic Systems, Aviation Computer-Integrated Complexes Department

References

M. Riesenhuber, “Object recognition in cortex: Neural mechanisms, and possible roles for attention,” Department of Neuroscience Georgetown University Medical Center, Washington, DC, 2007.

Y. Lecun and Y. Bengio, Convolutional Networks for Images, Speech, and Time-series, in Arbib, M. A. (Eds), The Handbook of Brain Theory and Neural Networks, MIT Press, 1995.

Y. LeCun, L. Bottou, Y. Bengio and P. Haffner, “Gradient-Based Learning Applied to Document Recognition.” Proceedings of the IEEE, 1998.

Downloads

How to Cite

Sineglazov, V. M., & Hotsyanivskyy, V. P. (2016). Image processing with liver mri convolutional neural network. Electronics and Control Systems, 4(50), 36–40. https://doi.org/10.18372/1990-5548.50.11384

Issue

Vol. 4 No. 50 (2016)

Section

THEORY AND METHODS OF SIGNAL PROCESSING

License

The scientific journal “Electronics and control systems” adheres to the principles of Open Access and provides free, immediate, and permanent access to all published materials without financial, technical, or legal barriers for readers.

All articles are published in Open Access under the Creative Commons Attribution 4.0 International (CC BY 4.0) license.

Copyright

Authors who publish their works in the journal “Electronics and control systems”:

  • retain the copyright to their publications;

  • grant the journal the right of first publication of the article;

  • agree to the distribution of their materials under the CC BY 4.0 license;

  • have the right to reuse, archive, and distribute their works (including in institutional and subject repositories), provided that proper reference is made to the original publication in the journal.