Method and Software Tool for Generating Artificial Databases of Biomedical Images Based on Deep Neural Networks

Oleh Berezsky; Petro Liashchynskyi; Oleh Pitsun; Grygoriy Melnyk

Method and Software Tool for Generating Artificial Databases of Biomedical Images Based on Deep Neural Networks

Machine Learning 2024-05-28 v1 Image and Video Processing

Authors: Oleh Berezsky , Petro Liashchynskyi , Oleh Pitsun , Grygoriy Melnyk

Abstract

A wide variety of biomedical image data, as well as methods for generating training images using basic deep neural networks, were analyzed. Additionally, all platforms for creating images were analyzed, considering their characteristics. The article develops a method for generating artificial biomedical images based on GAN. GAN architecture has been developed for biomedical image synthesis. The data foundation and module for generating training images were designed and implemented in a software system. A comparison of the generated image database with known databases was made.

Keywords

generative adversarial network image generation synthetic data generation

Cite

@article{arxiv.2405.16119,
  title  = {Method and Software Tool for Generating Artificial Databases of Biomedical Images Based on Deep Neural Networks},
  author = {Oleh Berezsky and Petro Liashchynskyi and Oleh Pitsun and Grygoriy Melnyk},
  journal= {arXiv preprint arXiv:2405.16119},
  year   = {2024}
}

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CEUR Workshop Proceedings (CEUR-WS.org). IDDM'2023: 6th International Conference on Informatics & Data-Driven Medicine, November 17 - 19, 2023, Bratislava, Slovakia

Method and Software Tool for Generating Artificial Databases of Biomedical Images Based on Deep Neural Networks

Abstract

Keywords

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