Microorganisms such as bacteria and fungi play essential roles in many application fields, like biotechnique, medical technique and industrial domain. Microorganism counting techniques are crucial in microorganism analysis, helping biologists and related researchers quantitatively analyze the microorganisms and calculate their characteristics, such as biomass concentration and biological activity. However, traditional microorganism manual counting methods, such as plate counting method, hemocytometry and turbidimetry, are time-consuming, subjective and need complex operations, which are difficult to be applied in large-scale applications. In order to improve this situation, image analysis is applied for microorganism counting since the 1980s, which consists of digital image processing, image segmentation, image classification and suchlike. Image analysis-based microorganism counting methods are efficient comparing with traditional plate counting methods. In this article, we have studied the development of microorganism counting methods using digital image analysis. Firstly, the microorganisms are grouped as bacteria and other microorganisms. Then, the related articles are summarized based on image segmentation methods. Each part of the article is reviewed by methodologies. Moreover, commonly used image processing methods for microorganism counting are summarized and analyzed to find common technological points. More than 144 papers are outlined in this article. In conclusion, this paper provides new ideas for the future development trend of microorganism counting, and provides systematic suggestions for implementing integrated microorganism counting systems in the future. Researchers in other fields can refer to the techniques analyzed in this paper.
Magnetic Resonance Materials in Physics, Biology and Medicine - To evaluate the placental function by monoexponential, biexponential, and diffusion kurtosis MR imaging (MRI) in patients with... 相似文献
The computational fluid dynamics (CFD) and kinetic-based moment methods coupled approach is adopted to simulate the bulk copolymerization of styrene–acrylonitrile (SAN) in a stirred tank reactor. Numerical simulations are carried out to investigate the impacts of impeller speed, monomer ratio, initiator ratio, and initial reaction temperature on the copolymerization process and product properties. Particularly, the Chaos theory is selected as a criterion for evaluating the occurrence of the thermal runaway. The Flory's and Stockmayer's distributions are employed to calculate chain length distribution and copolymer composition distribution of copolymer. The simulation results highlight that the appearance of thermal runaway can be postponed by properly increasing the rotation speed, decreasing the initiator loadings, initial acrylonitrile contents and initial reactor temperature. Furthermore, significant differences exist in the product properties that predicted by the ideal and non-ideal models, which demonstrates that the temperature heterogeneity plays a crucial role in SAN copolymerization. This study could offer references for the safe operation and design of polymerization processes. 相似文献