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Microorganisms are widely distributed in the human daily living environment.They play an essential role in environmental pollution control, diseaseprevention and treatment, and food and drug production. The analysis ofmicroorganisms is essential for making full use of different microorganisms.The conventional analysis methods are laborious and time-consuming. Therefore,the automatic image analysis based on artificial neural networks is introducedto optimize it. However, the automatic microorganism image analysis faces manychallenges, such as the requirement of a robust algorithm caused by variousapplication occasions, insignificant features and easy under-segmentationcaused by the image characteristic, and various analysis tasks. Therefore, weconduct this review to comprehensively discuss the characteristics ofmicroorganism image analysis based on artificial neural networks. In thisreview, the background and motivation are introduced first. Then, thedevelopment of artificial neural networks and representative networks arepresented. After that, the papers related to microorganism image analysis basedon classical and deep neural networks are reviewed from the perspectives ofdifferent tasks. In the end, the methodology analysis and potential directionare discussed.

Applications of Artificial Neural Networks in Microorganism Image  Analysis: A Comprehensive Review from Conventional Multilayer Perceptron to  Popular Convolutional Neural Network and Potential Visual Transformer