Method and device for AI training and analysis of hydrothorax and ascites detection

By using AI training methods to perform image recognition and annotation on pleural and peritoneal fluid samples, and combining urine and pleural and peritoneal fluid feature datasets, the problem of tangible object classification and quantitative analysis in pleural and peritoneal fluid detection was solved, achieving efficient and accurate identification and quantitative analysis, and improving the recognition capability of the AI ​​model.

CN120953983APending Publication Date: 2025-11-14SHENZHEN ANLV MEDICAL TECH CO LTD
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Patent Information

Application Number
CN202410592889.0
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-05-14
Publication Date
2025-11-14

AI Technical Summary

Technical Problem

In existing technologies, it is difficult to achieve accurate classification and quantitative analysis of tangible matter in pleural and peritoneal fluid detection, especially when a high proportion of strongly fluorescent cells are present, which may lead to missed detection of tumor cells. Furthermore, bacterial detection relies on manual staining and microscopic examination, which carries the risk of misjudgment and missed detection.

Method used

AI training methods were used to perform image recognition and annotation on microscopic samples. By combining AI feature datasets for urine and pleural and peritoneal fluid detection, training efficiency and accuracy were improved through preprocessing and manual review, including bacterial culture and staining.

Benefits of technology

It enables accurate classification and quantitative analysis of tangible substances in pleural and peritoneal fluid, improves the efficiency and accuracy of AI recognition, reduces engineering difficulty, and ensures the efficiency of feature data acquisition and continuous iteration of recognition capabilities.

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Abstract

According to the hydrothorax and ascites detection AI training and analysis method and device, a hydrothorax and ascites sample is preprocessed to obtain a microscopic examination sample, and the microscopic examination sample is tiled; shooting to obtain a microscopic examination sample image; identifying and labeling tangible objects in the microscopic examination sample image to obtain a labeled picture; and AI training is carried out by using the labeled picture to obtain a hydrothorax and ascites detection AI feature data set A. An AI recognition algorithm of the urine AI feature data set is adopted, the chest and ascites tangible object image A is output, manual recheck recognition and labeling are carried out, and a labeling picture B is obtained; carrying out AI training by using the labeled picture B to obtain a hydrothorax and ascites detection AI feature data set B; and by adopting an AI recognition algorithm of the hydrothorax and ascites detection AI feature data set B or A, outputting a hydrothorax and ascites tangible object image C, carrying out manual recheck recognition and labeling, obtaining a labeling picture D, and carrying out AI training to obtain a hydrothorax and ascites detection AI feature data set C. Through AI training, tangible objects in the hydrothorax and ascites turbid liquid can be accurately classified and identified.
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