Use of Image Analysis Methods and Mathematical Statistics Methods as Tools for Assessing Toxicity of Nanoscale Materials

DOI

10.2991/aisr.k.201029.068How to use a DOI?

Keywords

Toxicology, Ecotoxicology, Image Analysis, Microscopy, Nanoscale Materials, Statistics

Abstract

The results of the study of biological materials are often represented by images. The images carry a lot of information important for analysis, but at the same time, it becomes difficult to interpret this information. The problem of interpretation lies in the fact that it is influenced by the personal experience of the researcher to a large extent, therefore the search for methods of objective assessment of images is relevant in the field of biological sciences. Mathematical processing is the most rational way to increase the reliability of the evaluation of the research results in the visualization of images. The article systematizes the most common methods of image analysis in the practice of biological, environmental, and toxicological studies, which give a calculable result suitable for analysis by methods of mathematical statistics. The approaches that allow interpreting color data of images are presented in detail. There are given examples of using various approaches to schematization in the graphical information analysis with further processing by methods of descriptive, parametric and non-parametric statistics.

Copyright

© 2020, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Anna M. Ignatova
AU  - Marina A. Zemlyanova
PY  - 2020
DA  - 2020/11/10
TI  - Use of Image Analysis Methods and Mathematical Statistics Methods as Tools for Assessing Toxicity of Nanoscale Materials
BT  - Proceedings of the 8th Scientific Conference on Information Technologies for Intelligent Decision Making Support (ITIDS 2020)
PB  - Atlantis Press
SP  - 365
EP  - 368
SN  - 1951-6851
UR  - https://doi.org/10.2991/aisr.k.201029.068
DO  - 10.2991/aisr.k.201029.068
ID  - Ignatova2020
ER  -