Cell image analysis method combining morphology and color analysis and application and instrument thereof
Through the U-Net network model combining morphology and color analysis, the problem of large and inaccurate workload and inaccurate detection of cell activity is solved by the U-Net network model, and efficient and accurate quantitative analysis of cell information is achieved.
CN119723569APending Publication Date: 2025-03-28博溪生物科技(苏州)有限公司
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Patent Information
- Application Number
- CN202411616021.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-13
- Publication Date
- 2025-03-28
AI Technical Summary
Technical Problem
Traditional MTT colorimetry has problems such as large workload and inaccurate experimental results when detecting cell activity, and organic solvents are harmful to the experimenter.
Method used
The U-Net network model is used to combine morphology and color analysis with cell image analysis. The cell-generated formazan crystal content is automatically analyzed through image recognition technology and morphological changes are classified, so as to achieve efficient and accurate detection without manual intervention.
Benefits of technology
It improves the accuracy and repetition of quantitative analysis of cell information, shortens the experimental cycle, reduces manual intervention, and provides richer cellular information than traditional colorimetric methods.
✦ Generated by Eureka AI based on patent content.
Abstract
The invention provides a form and color analysis combined cell image analysis method and application and instrument thereof, and belongs to the technical field of artificial intelligence. The method comprises the following steps: S1, acquiring an image sample; s2, image data preprocessing: carrying out key area cutting and size standardization operation on all collected image samples; step S3, image data annotation: carrying out centroid point selection and classification annotation on the image samples of which the sizes are adjusted; s4, establishing a cellular morphology segmentation and classification model based on the U-Net network model, and performing network training; and S5, verifying the identification effect and precision of the network on the cell information by using the verification set and the test set. The technical scheme of the invention can realize multi-dimensional analysis, is convenient, efficient and non-toxic, has the characteristics of high precision, high automation degree, strong expansibility and the like, and has a very good practical application value.
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