Medical image recognition method, device and equipment, and storage medium

Abstract

The invention relates to the field of artificial intelligence, and discloses a medical image recognition method, device and equipment, and a storage medium. The method, the device and the equipment are applied to the field of smart medical treatment, and are used for improving the medical image recognition efficiency. The method comprises the following steps: receiving an initial image sent by a user terminal; classifying the initial image, and determining the image type of the initial image; when the initial image is a medical feature image, performing image segmentation on the medical feature image through a preset double-attention network model to obtain a medical foreground image; correcting the medical foreground image to obtain a corrected medical foreground image; performing text detection on the corrected medical foreground image to obtain a target text; performing character recognition on the target text to obtain a recognized field; correcting and checking the index field inthe identified field to obtain a corrected field; and classifying the corrected field to obtain a classification result, and sending the classification result to the target terminal.

Description

technical field [0001] The present invention relates to the field of medical image recognition, in particular to a medical image recognition method, device, equipment and storage medium. Background technique [0002] For a long time, the uneven distribution of medical resources in our country, the difficulty and high cost of seeing a doctor, and other problems have been plaguing the people. With the promotion of the national medical reform process, the mobile medical market operation has emerged. Thanks to the popularization of the concept of knowledge payment and the liberalization of medical e-commerce policies, the market size of the mobile medical industry has grown rapidly, and the number of online consultations by users has also increased rapidly. [0003] However, when users make online consultations, they usually need to take and upload historical clinical examination reports for online diagnosis and treatment by doctors. A large number of unclassified photos will g...

AI Technical Summary

Problems solved by technology

A large number of unclassified photos will greatly reduce the diagnosis and treatment efficiency of online doctors and cause diagnostic errors

[0004] The existing solution is to use a recognition model for a single image of a determined category, without considering the situation where users upload a large number of different inspection reports, the existing recognition model cannot accurately identify the text data in the report

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