Abstract
Cell segmentation is an important direction in biological and medical image processing. As a new image segmentation method, U2-Net not only has a better segmentation effect, but also has a better segmentation effect on adherent cells than traditional cell segmentation methods. This paper presents a U2-Net based cell segmentation method, analyses the structure and innovation of the algorithm, puts forward an effective execution process, trains and measures the results through pixel accuracy and loss function, selects the optimal model for cell image segmentation. After experiments, the effect of cell division is remarkable, and representative results of cell division are obtained.
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