Abnormal cell screening method and system based on image analysis

By obtaining staining parameters of cell sections through image analysis, fitting and standardizing the staining curves, the problem of inaccurate staining characteristics caused by individual cell differences is solved, thereby improving the accuracy of cell screening and diagnostic consistency.

CN121392834BActive Publication Date: 2026-05-01BASHANHONG (BEIJING) PHARMACEUTICAL TECHNOLOGY CO LTD
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Patent Information

Application Number
CN202511547948.3
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2025-10-28
Publication Date
2026-05-01
Estimated Expiration
2045-10-28

AI Technical Summary

Technical Problem

Traditional cell screening methods suffer from variations in staining characteristics due to individual cell differences, which affects the accuracy of screening. In particular, differences in staining conditions and equipment between different laboratories affect diagnostic consistency.

Method used

By acquiring continuous image frames of cell slices, extracting staining parameters and performing standardized correction, and using image analysis methods to fit staining curves to eliminate the influence of individual differences, an abnormal cell screening method using image analysis is adopted, including acquiring staining parameters, fitting curves, standardization correction, and threshold comparison.

Benefits of technology

It improves the accuracy of abnormal cell screening, reduces the differences in staining sensitivity caused by biological factors such as individual gene expression, cell membrane protein composition and pH changes, and enhances diagnostic consistency.

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Abstract

The application relates to the technical field of image processing, in particular to an abnormal cell screening method and system based on image analysis, which comprises the following steps: acquiring continuous image frames of a staining process, extracting average optical density, integral optical density and chromatin gray standard deviation of sample cells as staining parameters, and acquiring chromatin texture; forming a staining parameter space curve with the change of the staining parameters over time, fitting to obtain a continuous staining curve; aligning and fitting the continuous staining curve with a standard parameter curve calibrated in advance to obtain a coordinate transformation vector; acquiring an image frame after the completion of the staining, performing standardization correction on the staining parameters of the to-be-tested cells by using the coordinate transformation vector to obtain chromatin texture features, and then performing feature comparison and identification on abnormal cells. The application reduces the staining sensitivity difference caused by biological factors such as individual gene expression difference, different cell membrane protein compositions and pH value changes, and eliminates the influence of staining condition difference and equipment difference among different laboratories on the screening result.
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