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Using a Neural Network to Separate Lungs in X-Ray Images

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Bulletin of the Russian Academy of Sciences: Physics Aims and scope

Abstract

An auxiliary neural network is developed to solve the problem of preliminarily processing X-ray images to distinguish areas with lung and spine, and to mask unnecessary areas. Images processed with the neural network are used to study the main neural network for detecting pathology in lungs. A comparative analysis is performed of the quality of studying the main neural network on the basis of preliminarily processed images and initial ones.

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Funding

This work was supported by the RF Ministry of Education and Science, state task under project no. 8.8017.2017/BCh.

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Authors and Affiliations

  1. Kazan National Research Technical University (Tupolev-KAI), 420111, Kazan, Russia

    R. Sh. Minyazev & A. A. Rumyantsev

  2. Volga State Technical University, 424000, Yoshkar-Ola, Russia

    A. A. Baev & T. D. Baeva

Authors
  1. R. Sh. Minyazev
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  2. A. A. Rumyantsev
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  3. A. A. Baev
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  4. T. D. Baeva
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Corresponding author

Correspondence to A. A. Baev.

Additional information

Translated by Yu. Zikeeva

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Minyazev, R.S., Rumyantsev, A.A., Baev, A.A. et al. Using a Neural Network to Separate Lungs in X-Ray Images. Bull. Russ. Acad. Sci. Phys. 83, 1494–1497 (2019). https://doi.org/10.3103/S1062873819120153

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  • DOI: https://doi.org/10.3103/S1062873819120153

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