An image detection system and detection method in cell differentiation

Abstract

The invention belongs to the technical field of cell differentiation, and discloses an image detection system and detection method in cell differentiation. The image detection system in cell differentiation comprises a marker gene introduction module, an induced differentiation module, an image acquisition module, a main control module, an image identification module, an image segmentation module,a data storage module and a display module. The invention improves the accuracy and the recognition speed of the cell image recognition through the image recognition module, can realize the intelligent operation and judgment, can quickly identify the cell type state, and can help the doctor to quickly diagnose whether the cell is in the healthy state or not. At the same time, the image segmentation module screens the result of threshold segmentation, the incomplete cell nucleus is sent into adaptive segmentation for secondary segmentation, the complete cell nucleus image is directly output, and then the results of adaptive segmentation and blocking threshold segmentation are combined to form the final ideal output image.

Description

technical field [0001] The invention belongs to the technical field of cell differentiation, and in particular relates to an image detection system and a detection method in cell differentiation. Background technique [0002] Cell differentiation refers to the process in which cells from the same source gradually produce cell groups with different morphological structures and functional characteristics. The result is that cells are different in space, and the same cell is different from its previous state in time. . The essence of cell differentiation is the selective expression of the genome in time and space, through the switching on or off of the expression of different genes, and finally the production of signature proteins. In general, the process of cell differentiation is irreversible. However, under certain conditions, differentiated cells are also unstable, and their gene expression patterns can undergo reversible changes and return to their undifferentiated state...

AI Technical Summary

Problems solved by technology

The conventional OPT imaging algorithm only considers the absorption characteristics of biological tissues to photons, and can only reconstruct the absorption coefficient of photons but not the scattering coefficient of photons

When using OPT technology for imaging, the impact of scattering cannot be ignored, and will be mixed with the absorption characteristics of photons, resulting in the reduction of the traditional OPT imaging spatial resolution and inaccurate reconstruction results.

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