Medical images of breast tumors diagnostics with application of hybrid CNN–FNN network

Authors

  • Yuriy Zaychenko ESC "IASA" NTUU "Igor Sikorsky KPI", Kyiv, Ukraine https://orcid.org/0000-0001-9662-3269
  • G. Hamidov The Department of Information Technologies of Azerbaijanenergo, Baku, Azerbaijan
  • I. Varga ESC "IASA" NTUU "Igor Sikorsky KPI", Kyiv, Ukraine

DOI:

https://doi.org/10.20535/SRIT.2308-8893.2018.4.03

Keywords:

medical diagnostics, breast cancer classification, FNN, CNN, hybrid network, dimensionality reduction, PCM

Abstract

The problem of classification of breast tumors on medical images is con-sidered. For its solution the new class of convolutional neural networks-hybrid CNN–FNN network is developed in which convolutional neural network VGG-16 is used as the feature extractor while fuzzy neural network NEFClass is used as the classifier. Training algorithms of FNN were implemented. The experimental investigations of the suggested hybrid network on the standard data set were carried out and comparison with known results was performed. The problem of data dimensionality reduction is considered and application of PCM method is investigated.

Author Biographies

Yuriy Zaychenko, ESC "IASA" NTUU "Igor Sikorsky KPI", Kyiv

Yuriy Zaychenko,

Doctor of Technical Sciences, a professor at ESC "IASA" NTUU "Igor Sikorsky KPI", Kyiv, Ukraine.

G. Hamidov, The Department of Information Technologies of Azerbaijanenergo, Baku

Galib Hamidov,

Doctor of Philosophy (Ph.D.), the Director of the Department of Information Technologies of Azerbaijanenergo, Baku, Azerbaijan.

I. Varga, ESC "IASA" NTUU "Igor Sikorsky KPI", Kyiv

Igor Yuriyovych Varga,

ESC "IASA" NTUU "Igor Sikorsky KPI", Kyiv, Ukraine.

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Published

2018-12-18

Issue

Section

Progressive information technologies, high-efficiency computer systems