A Review of Image Analysis in Biochemical Engineering

Abstract

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.