Artificial intelligence identification method for peripheral hemolymph micronucleus cell image

Abstract

The invention provides an artificial intelligence identification method for a peripheral hemolymph micronucleus cell image, and the method comprises the steps: collecting a to-be-analyzed sample through a collection device, and obtaining a cell image; carrying out segmentation processing on the obtained cell image to obtain a foreground to-be-detected area; identifying, classifying and counting the cells on the foreground to-be-detected area; storing the cell type information on the foreground to-be-detected area and the position information of the foreground to-be-detected area on the cell image to form traceable information; and forming an image-text report according to the traceable information, and storing the image-text report as an artificial intelligence system learning training material. According to the artificial intelligence identification method for the peripheral hemolymph micronucleus cell image provided by the invention, automatic identification and classification of specific images of lymphoblasts, micronucleus cells and nude nuclei of peripheral blood can be realized. Compared with an existing microscope artificial microscopic examination method, the statistical accuracy is higher, and the detection speed is remarkably increased.

Description

technical field [0001] The invention relates to the field of lymphatic micronucleus cell inspection, in particular to an artificial intelligence recognition method for images of peripheral blood lymphatic micronucleus cells. Background technique [0002] Most of the human peripheral blood lymphocytes are in the G0 phase of the cell cycle. After in vitro culture in the medium containing PHA, the lymphocytes in the G0 phase can be transformed into lymphoblasts and restore their ability to divide. In the process of cell division, due to the influence of chemical substances or radiation, the chromosomes of lymphoblasts can be damaged, resulting in chromosome breakage, and the chromosome fragments without centromere cannot move with the chromosomes into the daughter cell nucleus, resulting in the formation of micronuclei in the cytoplasm. [0003] Therefore, the detection of peripheral blood lymphatic micronucleus cells is one of the must-test methods for judging radiation damage...

AI Technical Summary

Problems solved by technology

[0005] In order to solve the problems of heavy workload, low efficiency, and low traceability of results caused by the existing human eye detection method mentioned in the above background technology, the present invention provides an artificial intelligence recognition method for images of peripheral blood lymphatic micronucleus cells, It is characterized in that: the method steps are as follows:

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