A medical image recognition method, device, computer equipment and storage medium

Abstract

Embodiments of the present application provide a medical image recognition method, device, computer equipment, and storage medium. The method first acquires the original endoscopic image and endoscopic report information, and extracts pathological information from the endoscopic report information. Then, the original Endoscopic images are classified and recognized to obtain white light images and NBI images. Then, the white light images are input into the trained first neural network model for feature extraction to obtain the first feature set, and the NBI images are input into the trained second neural network. The model performs feature extraction to obtain the second feature. Finally, according to the pathological information, the first feature set, and the second feature, it uses the trained machine learning classifier to perform recognition, and obtains the recognition result of the endoscopic image. The fusion of multiple features of the original endoscopic image improves the recognition accuracy. At the same time, the machine learning classifier is used for recognition, which makes the recognition result more objective and greatly improves the recognition efficiency of medical images.

Description

technical field [0001] The present application relates to the technical field of medical image processing, in particular to a medical image recognition method, device, computer equipment and storage medium. Background technique [0002] Endoscopic image refers to the medical electronic optics that integrates high-tech technologies such as light, machinery, and electricity, which can be inserted into human body cavities and visceral cavities for direct observation, diagnosis, and treatment. The processed image output by the instrument is convenient for doctors to identify and diagnose according to the endoscopic image of the electronic endoscope. However, manual identification has high requirements for endoscopists, which is subjectivity, low efficiency, and professional doctors are required problem of identification. Contents of the invention [0003] Embodiments of the present application provide a medical image recognition method, device, computer equipment, and storage...

AI Technical Summary

Problems solved by technology

[0003] The embodiment of the present application provides a medical image recognition method, device, computer equipment and storage medium to solve the technical problem of low recognition efficiency in manual recognition

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