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A Brief Review for Content-Based Microorganism Image Analysis Using Classical and Deep Neural Networks

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Information Technology in Biomedicine (ITIB 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 762))

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Abstract

Microorganisms play very important roles in people’s daily life. To discover the information of them is a fundamental work in microbiological studies, which can assist microbiologists and related scientists to get to know more properties, habits and characteristics of these tiny but obbligato living beings. To this end, effective Content-based Microorganism Image Analysis (CBMIA) approaches using Artificial Neural Networks (ANNs) are introduced to microbiological fields from the 1990s. In order to clarify the development history and find the developing trend of ANNs in the CBMIA field, we briefly survey around 60 related works in this paper, including classical ANNs, deep ANNs and methodology analysis.

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Notes

  1. 1.

    DGM LIB: Semantic Image Segmentation with Conditional Random Fields. 2018, Available at: http://research.project-10.de/dgm/.

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Acknowledgement

We thank our previous cooperators in related works: Prof. Dr.-Ing. Marcin Grzegorzek, Dr.-Ing. Kimiaki Shirahama, Dr.-Ing. Joanna Czajkowska, M.Sc. Sergey Kosov, Dr.-Ing. Fangshu Ma, Prof. Yanling Zou and Prof. Dr. Beihai Zhou. We also thank the ‘Double Top Construction’ funding supported by the Northeastern University, China.

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Authors and Affiliations

  1. Northeastern University, Shenyang, China

    Chen Li, Shouliang Qi, Fangfang Han, Wei Qian & Xin Zhao

  2. Liaoning Shihua University, Fushun, China

    Ning Xu

  3. Chengdu University of Information Technology, Chengdu, China

    Tao Jiang

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  1. Chen Li
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  2. Ning Xu
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Correspondence to Xin Zhao .

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Editors and Affiliations

  1. Faculty of Biomedical Engineering, Silesian University of Technology, Zabrze, Poland

    Ewa Pietka

  2. Faculty of Biomedical Engineering, Silesian University of Technology, Zabrze, Poland

    Pawel Badura

  3. Faculty of Biomedical Engineering, Silesian University of Technology, Zabrze, Poland

    Jacek Kawa

  4. Faculty of Biomedical Engineering, Silesian University of Technology, Zabrze, Poland

    Wojciech Wieclawek

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Li, C. et al. (2019). A Brief Review for Content-Based Microorganism Image Analysis Using Classical and Deep Neural Networks. In: Pietka, E., Badura, P., Kawa, J., Wieclawek, W. (eds) Information Technology in Biomedicine. ITIB 2018. Advances in Intelligent Systems and Computing, vol 762. Springer, Cham. https://doi.org/10.1007/978-3-319-91211-0_1

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