Cervical cancer focus analysis method based on cell image recognition

A technology of image recognition and analysis method, which is applied in the field of image recognition, can solve the problems of not fully describing the local complex and changeable microstructure, reduce the recognition rate, etc., and achieve the effect of improving recognition performance and high degree of automation

Inactive Publication Date: 2018-11-09
WUHAN LANDING INTELLIGENCE MEDICAL CO LTD
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Problems solved by technology

[0004] In the prior art, when identifying cervical cancer lesions based on supervised learning methods, only single pixel information is considered in the feature extraction stage, or when context inform

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  • Cervical cancer focus analysis method based on cell image recognition

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[0020] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of them. Based on the embodiments of the present invention, all other embodiments obtained by a person of ordinary skill in the art without creative work shall fall within the protection scope of the present invention.

[0021] Such as figure 1 As shown, the cervical cancer lesion analysis method based on cell image recognition of the present invention includes the following steps:

[0022] S1: Perform image enhancement on the image of cervical cancer lesion cells. Specifically, using histogram equalization and Gaussian filtering technology for image enhancement; by synthesizing the color information and position information of local neighboring pixels, the entire image is divided into su...

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Abstract

The invention puts forward a cervical cancer focus analysis method based on cell image recognition. The cervical cancer focus analysis method of the invention has the beneficial effects that: pixel grade features with abundant feature expression and super pixel grade features with certain semantic features are combined to obtain level grade features, then the level grade features are used for training a random forest to perform segmentation of cells, thereby well describing a microstructure with intricate and complex parts, and improving a recognition performance; in addition, automatic analysis is performed on an image from a cell level grade, a cervical cancer focus can be captured accurately, thus targeted treatment can be performed, and a high automation degree is achieved.

Description

technical field [0001] The invention relates to the field of image recognition, in particular to a method for analyzing cervical cancer lesions based on cell image recognition. Background technique [0002] The 300 million women in China need regular cervical cancer screening, and the coverage rate of 20% of the population has not yet been reached, which is still far from the goal of 80% of the population coverage required for cervical cancer prevention and control. [0003] At present, China lacks cytopathologists. Automated and cloud diagnosis can solve the problem of lack of pathologists in China, and provide accurate and objective diagnostic reports for cervical cancer examination. In recent years, machine learning methods based on supervised learning have been increasingly used in the analysis of cervical cancer lesions, and have achieved good recognition results. This method is mainly divided into two steps: feature extraction and pattern recognition. The quality of f...

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Application Information

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IPC IPC(8): G06K9/62G06T5/40G06T7/136
CPCG06T5/40G06T7/136G06T2207/30024G06T2207/10056G06T2207/30096G06V2201/03G06F18/2415
Inventor 庞宝川孙小蓉汪键曹得华
Owner WUHAN LANDING INTELLIGENCE MEDICAL CO LTD
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