Summary of Method and Software Tool For Generating Artificial Databases Of Biomedical Images Based on Deep Neural Networks, by Oleh Berezsky et al.
Method and Software Tool for Generating Artificial Databases of Biomedical Images Based on Deep Neural Networks
by Oleh Berezsky, Petro Liashchynskyi, Oleh Pitsun, Grygoriy Melnyk
First submitted to arxiv on: 25 May 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Image and Video Processing (eess.IV)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper proposes a method for generating artificial biomedical images using Generative Adversarial Networks (GANs). The GAN architecture is developed for biomedical image synthesis, and a software system is designed to generate training images based on a data foundation. The generated image database is compared with known databases. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper creates fake medical images using special computer networks called GANs. It helps doctors and researchers by making more images available for testing new treatments and procedures. The method works by creating lots of different fake images that are similar to real ones, but not actually real. This can help with training AI systems or testing new medical ideas. |
Keywords
» Artificial intelligence » Gan » Image synthesis
