Intelligent abnormal cell judgment method and device and computer readable storage medium

Abstract

The invention relates to an artificial intelligence technology, and discloses an intelligent abnormal cell judgment method. The method comprises the steps of obtaining a cell set and a tag set, carrying out pretreatment operation on the cell set; based on a multi-threshold segmentation model, performing gray scale division on the cell set after the preprocessing operation is completed, obtaining amulti-stage gray level cell set; calculating a Hessian matrix based on the multistage grayscale cell set and obtaining a nine-channel cell set, inputting the nine-channel cell set and the label set into an abnormal cell judgment model for training; and after the abnormal cell judgment model meets a preset training quitting condition, quitting training, receiving a cell picture of the user, inputting the cell picture into the abnormal cell judgment model to judge whether the cell comprises an abnormal cell or not, and outputting a judgment result, thereby finishing intelligent abnormal cell judgment. The invention further provides an intelligent abnormal cell judgment device and a computer readable storage medium. According to the invention, an accurate intelligent abnormal cell judgment function can be realized.

Description

technical field [0001] The present invention relates to the technical field of artificial intelligence, in particular to an intelligent abnormal cell judging method, device and computer-readable storage medium. Background technique [0002] Abnormal cells, such as cancer cells, are often the trigger for major human diseases. According to surveys, there are 500,000 new cases and 274,000 deaths each year in the world, of which 85% of new cases are due to early recognition of abnormal cells The reason for the low recognition rate. In particular, cervical cancer is currently the only cancer that can be detected and cured early, so early identification is critical for the treatment of the disease. Cell fluid examination is currently the most commonly used method for identifying abnormal cells. However, due to the lack of pathologists and cell testing equipment in China, the identification rate for abnormalities is very low. In addition, there are various artificial identificatio...

AI Technical Summary

Problems solved by technology

Cell fluid examination is currently the most commonly used method for identifying abnormal cells. However, due to the lack of pathologists and cell testing equipment in China, the identification rate for abnormalities is very low. In addition, there are various artificial identification equipment systems, but most auxiliary identification systems Generally based on traditional methods, which rely on precise segmentation of cytoplasm or nucleus and traditional image processing algorithms for feature extraction and selection, so the pre-processing of recognition is cumbersome, and the recognition rate is not high

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