As bioprocessing moves forward, many projects explore new assays and sensors, but imaging is not discussed as often as it deserves. In a special issue of Applied Sciences that focused on using imaging in biotechnology and bioprocessing, guest editor Sang-Kyu Jung, PhD, reported that “image analysis is frequently applied in the fields of biotechnology and bioprocess engineering, where various imaging devices are used for research and development.”

As an expert in remote sensing and image analysis, as well as an associate professor of biological and chemical engineering at Hongik University in Sejong, Republic of Korea, Jung understands the potential of imaging in bioprocessing. “Compared to manual methods performed by humans, automated image analysis allows for fast, accurate, and reliable quantitative analysis,” he noted.

As one example of researchers applying image analysis to bioprocessing, consider the recent report from Jean-Sébastien Guez, PhD, a senior scientist at the Institut Pascal in Clermont-Ferrand, France, and his colleagues. This team of scientists used in situ microscopy to classify morphological features of cells. As Guez and his colleagues explained, this technology could be a “new tool for the study of heterogeneity during cultivation processes in [a] bioreactor, at the industrial scale or for research purposes.” As these scientists emphasized, this image analysis of in situ microscopy provides “a new noninvasive online monitoring technique.”

Making the most of imaging in bioprocessing, however, depends on applying advanced analytical techniques. For example, Jung noted that “recent advancements in machine learning techniques have made it possible to better utilize existing image analysis results.” In particular, he pointed out that the combination of advanced algorithms and computers equipped with graphics processing units (GPUs), which were developed for image analysis, improves the detection and interpretation of objects in images. Nonetheless, he added that “there is a need for the development of user-friendly image analysis software.”

As with any technology, its penetration in an industry often depends on a combination of power and simplicity. Consequently, advanced image analysis might eventually be applied to many more bioprocessing steps.

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