Методы сверхразрешения в задачах анализа медицинских изображений

Д М Суходолов; А А Крыловецкий

doi:10.17308/sait.2018.1/1200

Методы сверхразрешения в задачах анализа медицинских изображений

Authors

Д М Суходолов Voronezh State University
А А Крыловецкий Voronezh State University

DOI:

https://doi.org/10.17308/sait.2018.1/1200

Keywords:

detector, descriptor, superresolution, interpolation, digital image processing, image analysis

Abstract

The effectiveness of methods of superresolution in the problems of analysis of medical images and machine learning is investigated. A comparative analysis of the results of the search for singular points on the original and doubled by the methods of interpolation and su-perresolution images is carried out. Various combinations of modern detectors and descriptors of singular points are considered.

Author Biographies

Д М Суходолов, Voronezh State University

Graduate student of the Department of digital technology, Voronezh State University.
А А Крыловецкий, Voronezh State University

Ph.D. in Physics and Mathematics, Associate Professor of Department of Digital Technologies, Voronezh State University.

References

Downloads

PDF (Russian)

Published

2018-03-11

Issue

No. 1 (2018): January - March

Section

Intelligent Information Systems

License

Условия передачи авторских прав in English

How to Cite

Методы сверхразрешения в задачах анализа медицинских изображений. (2018). Proceedings of Voronezh State University. Series: Systems Analysis and Information Technologies, 1, 126-132. https://doi.org/10.17308/sait.2018.1/1200