The Study on Computer Vision-Assisted Cell Bank Construction and Screening & Classification

Computer vision technology plays an important role in screening and culturing cells. This paper proposes a method to construct a helper cell library based on cell image segmentation and screening. Firstly, cell culture and image acquisition were carried out. The main content is to use laboratory conditions to carry out different cell types. Through careful observation of the whole process of cell proliferation and passage, the representative pictures of different stages were taken. Analysis and summary of the relevant morphology, texture, color characteristics. Secondly, computer vision technology is used to segment cells and extract the main features such as cell perimeter and area. Explore the automatic information extraction method of cell bank, and complete the image segmentation of individual cell image from the whole picture. Finally, the cells were screened and identified. Investigate different pattern recognition methods and neural network structures, and prepare pictures of various cell pictures. The corresponding neural network and prediction program are constructed. This paper proposes an automatic image processing method for each image category in cell culture cycle, which improves the automation of production process. At the same time, compared with the design of a single algorithm for a certain type of cell, different algorithm design ideas are proposed for three types of pictures with different characteristics, which is closer to the dynamic change of cell morphology in the process of cell culture. This research has important application prospects in promoting cell factory research, cell bank construction and automatic screening.