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Medical image recognition system and recognition method based on artificial intelligence

A medical imaging and artificial intelligence technology, applied in the field of medical imaging, can solve problems such as low recognition accuracy, improve the accuracy and save the recognition process.

Pending Publication Date: 2022-07-22
郏县人民医院
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  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to provide a medical image recognition system and recognition method based on artificial intelligence, which is used to solve the problem that the existing medical image recognition system adopts a unified standard for recognition of medical images obtained by scanning with different parameters, resulting in low recognition accuracy;

Method used

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Embodiment 1

[0036] like figure 1 As shown, a medical image recognition system based on artificial intelligence includes an image acquisition module, an image detection module, a normalization processing module and a treatment evaluation module; the image acquisition module, the image detection module, the normalization processing module and the treatment evaluation module are connected in sequence .

[0037]The image acquisition module is used to automatically collect and identify the images of the lesion area that the patient needs to examine. The image of the lesion area that the patient needs to examine is acquired by a CT scanner. The CT scanner is a full-featured disease detection instrument, which is an electronic computer. X-ray tomography technology for short, the working process of the CT scanner includes: according to the difference in the absorption and transmittance of X-ray by different tissues of the human body, the human body is measured with a highly sensitive instrument, ...

Embodiment 2

[0042] like figure 2 As shown, an artificial intelligence-based medical image recognition method includes the following steps:

[0043] Step 1: Based on the medical image recognition system of the part to be detected of the patient, by aligning the image acquisition module with the part to be inspected by the patient, the image of the lesion area of ​​the patient is automatically collected and recognized;

[0044] Step 2: The image detection module performs resolution detection on the lesion area of ​​the patient collected and identified in Step 1 to obtain the display coefficient of the sample image, and judges the resolution detection result by comparing the display coefficient with the display threshold value, and determines the resolution detection result. Unqualified lesion images are eliminated;

[0045] Step 3: The normalization processing module normalizes the remaining lesion images in step 2 to obtain the magnification factor, determines the magnification factor fo...

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Abstract

The invention belongs to the field of medical images, relates to an image recognition technology, and is used for solving the problem of low recognition precision caused by the fact that an existing medical image recognition system recognizes medical images obtained through scanning of different parameters by adopting a unified standard, in particular to a medical image recognition system and recognition method based on artificial intelligence. Comprising an image acquisition module, an image detection module, a normalization processing module and a treatment evaluation module, the image acquisition module, the image detection module, the normalization processing module and the treatment evaluation module are connected in sequence; according to the invention, the image detection module detects the resolution of the collected medical image and obtains the display coefficient, and the scanning effect of the CT scanner is judged through the numerical value of the display coefficient, so that the image with the unqualified resolution is removed from a batch of sample images, the recognition process of the medical image with the unqualified resolution is saved, and the recognition efficiency of the medical image with the unqualified resolution is improved. And re-scanning the image with the unqualified resolution.

Description

technical field [0001] The invention belongs to the field of medical imaging and relates to an image recognition technology, in particular to a medical image recognition system and recognition method based on artificial intelligence. Background technique [0002] In medical imaging, AI has demonstrated its ability to improve the efficiency of image analysis by quickly and accurately labeling specific abnormal structures for reference by radiologists. In 2011, researchers at NYU LangoneHealth found that this type of automated analysis could find and match specific lung nodules 62 to 97 percent faster than radiologists. The findings suggest that this AI-enabled image analysis efficiency could save radiologists $3 billion a year by freeing up more time to focus on reviewing content that requires more interpretation or judgment. The latest research also explores the exploration of artificial intelligence in pharmaceuticals, molecular structure and biological proteins. These exc...

Claims

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Application Information

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IPC IPC(8): G06T7/00G16H20/00G16H50/70
CPCG06T7/0012G16H20/00G16H50/70G06T2207/10081G06T2207/30096
Inventor 尹培红
Owner 郏县人民医院
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