A Review of Image Analysis in Biochemical Engineering

The purpose of image analysis is to extract useful information from images. Since modern image analysis allows fast, accurate, and reliable quantitative analysis, it is widely used at present in many areas of research and development. In this article, I review the image analysis methods that are com...

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Bibliographic Details
Published inBiotechnology and bioprocess engineering Vol. 24; no. 1; pp. 65 - 75
Main Author Jung, Sang-Kyu
Format Journal Article
LanguageEnglish
Published Seoul The Korean Society for Biotechnology and Bioengineering 01.02.2019
Springer Nature B.V
한국생물공학회
Subjects
Algorithms
Animals
Biochemical engineering
biocompatible materials
Bioengineering
biomass
Biomaterials
Biomedical materials
Biotechnology
Chemical engineering
Chemistry
Chemistry and Materials Science
Computer peripherals
densitometry
Digital cameras
Digital imaging
Image analysis
Image processing
Industrial and Production Engineering
Information processing
Machine learning
Microscopy
Morphology
phenotype
Phenotyping
Quantitative analysis
R&D
Research & development
research and development
Review Paper
Software packages
생물공학
image processing
binarization
machine learning
morphology analysis
densitometric analysis
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Summary:The purpose of image analysis is to extract useful information from images. Since modern image analysis allows fast, accurate, and reliable quantitative analysis, it is widely used at present in many areas of research and development. In this article, I review the image analysis methods that are commonly used in biochemical engineering, for which the subjects of the image analysis vary from molecules or cells to whole animals or biomaterials. Images captured by imaging hardware, which is not limited to digital cameras, are processed in multiple steps by applying various image processing algorithms to extract quantitative features. Image analysis has been successfully applied in diverse applications, ranging from simple densitometric evaluation to animal phenotyping and biomass analysis. Although machine learning is poised to become an increasingly common method of image analysis, traditional methods utilizing blob extraction from binarized images are likely to remain in use for the foreseeable future.
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ISSN:1226-8372
1976-3816
DOI:10.1007/s12257-018-0372-8