Intelligent canceration cell identification system and method, cloud platform, server and computer

Abstract

The invention belongs to the technical field of medical image identification and discloses an intelligent canceration cell identification system and a method thereof, a cloud platform, a server and acomputer, which comprise an image acquisition module, a front-end processing module, an expert cloud platform, a diagnosis and suggestion module and a display module. The image acquisition module is used for acquiring the image information of a to-be-identified cell specimen. The front-end processing module is used for carrying out the compression processing on the acquired image data of the to-be-identified cell specimen. The expert cloud platform is used for building a software platform on a cloud server side to establish an image analysis system, establishing a cell image training databaseby utilizing a deep learning convolutional neural network, identifying the acquired image information to find out determined lesion cells, and outputting the determined lesion cells to the display module. The diagnosis and suggestion module is used for displaying a symptom result, uploading the result to the expert cloud platform and providing the condition identification reference information with a certain maximum probability. The display module is used for displaying the symptom result which is accurately identified. According to the invention, a lot of manual time is saved and the missed diagnosis rate is further reduced. Meanwhile, the labor cost is reduced.

Description

technical field [0001] The invention belongs to the technical field of medical image recognition, and in particular relates to an intelligent cancerous cell recognition system and method, a cloud platform, a server, and a computer. Background technique [0002] In medicine, cancer refers to a malignant tumor originating from epithelial tissue, which is the most common malignant tumor. According to the "2015 China Cancer Statistics" report, from 2000 to 2011, the incidence of tumors in the male population was relatively stable, with an annual increase of about 0.2%; the incidence of tumors in the female population increased by about 2.2% each year; that is, in The female population showed a significant upward trend year by year. The International Union Against Cancer believes that 1 / 3 of cancers can be prevented, 1 / 3 of cancers can be cured if diagnosed early, and 1 / 3 of cancers can relieve pain and prolong life. Cervical cancer is one of the two most common malignant tumor...

AI Technical Summary

Problems solved by technology

[0004] To sum up, the problem in the prior art is that existing cervical cell recognition methods cannot distinguish between objects of cell images of specific cell types or cell images of uninteresting cell types, and for fusion (adjacent Individual cell identification in images of cell populations (or overlapping) may be ineffective, unable to detect the entire edge surrounding the object; using the SVM algorithm is difficult to implement for large-scale training samples

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