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To solve the problem of accurate identification of gas and liquid phases in gas-liquid two-phase flow, an image segmentation method based on deep convolutional neural network was proporsed. Firstly, the advantages and disadvantages of four image denoising methods and five image segmentation methods were compared. Secondly, the synthetic images were processed by image denoising and image segmentation, and the segmentation results were quantified by image segmentation evaluation indexes. Finally, image denoising and image segmentation were carried out on the public dataset images and the real gas-liquid two-phase flow images. The experimental results show that anisotropic diffusion filter, median filter, total variance filter and non-local mean filter have slightly different noise reduction performance on the bubble images, and non-local mean filter has the best effect. When the convolutional …