Medical image information identification method, device and system based on multiple neural networks

Abstract

The invention provides an information identification method based on multiple neural networks. The method comprises the following steps: inputting a medical image as an input image into a first neuralnetwork model to obtain first identification information; inputting the medical image as an input image into a second neural network model to obtain second identification information; when the firstidentification information is different from the second identification information, outputting an exception report and recording the number of times of the exception report; and adjusting a first parameter of the first neural network model and a second parameter of the second neural network model according to the frequency of the exception report. According to the method, device and system, at least two neural networks are superposed to reduce the false identification rate, the parameters of the neural network model are adjusted according to the difference of multiple identification results, and then the multiple neural network models are used for image identification, so that the false identification rate is evaluated and the model is optimized while the identification error rate is reduced, the occurrence of mismatching of medical reports is reduced, and medical disputes are avoided.

Description

technical field [0001] The present invention relates to the technical field of information identification, in particular to a method, device and system for identifying medical image information based on a multi-neural network. Background technique [0002] The self-service printing system obtains patient films from imaging workstations such as DR, CT, MR, and PACS, and obtains patient information and patient reports such as patient names, mobile phone numbers, barcode numbers, medical card numbers, and ID card numbers from PACS reporting workstations, and passes specific rules. Match the patient's film to the report. Patients need to print out the corresponding film and report after swiping the barcode / swiping the doctor card / swiping the ID card. [0003] This report printing method increases the patient's waiting time for picking up the film, and if the patient's film information is directly sent to the patient or doctor, it is necessary to perform image recognition on the...

AI Technical Summary

Problems solved by technology

[0005] For the image recognition performed by OCR in the prior art, it is only considered to improve the recognition accuracy rate, but even if the recognition accuracy rate is improved, it is impossible to achieve 100% recognition accuracy, and it is impossible to know whether a recognition error has occurred during the recognition process, let alone correct The identification process is corrected

As a result, medical images are taken by mistake, and information errors such as names are usually not known until the doctor and / or patient hands, increasing doctor-patient disputes

When manual adjustments are introduced after human errors are discovered, efficiency will be reduced

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