Corona virus disease 2019 screening method and system based on deep learning

Abstract

The invention discloses a corona virus disease 2019 screening method and system based on deep learning. The corona virus disease 2019 screening method comprises the steps: detecting a lung lesion areaof CT by using a deep learning detection model, and conveying the lung lesion area of CT into a three-classification network, wherein three classifications comprise COVID-19, influenza A and non-infection symptoms; and through calculation processing, outputting a CT diagnosis result and a disease probability. According to the method, based on deep learning, characteristics of CT images are automatically learned to distinguish COVIDI-19, influenza A and healthy people, so that the method is high in accuracy, the overall accuracy of current testing reaches 86.7%, the diagnosis speed is high, and only 30-60 S is needed for one set of CT according to different slice numbers; and a user can upload a CT image file and calculate and output a CT diagnosis result and the disease probability through the corona virus disease 2019 screening system, so that operation is convenient, the speed is high, and the detection rate of COVID-19 is greatly increased.

Description

technical field [0001] The invention belongs to the field of medical technology, and in particular relates to a deep learning-based screening method for COVID-19 and a screening system for COVID-19. Background technique [0002] In the early screening of the new type of coronavirus pneumonia (COVID-19), at present, it is mainly detected by means of kits, but its detection rate is low. In order to improve the detection rate of early screening of COVID-19, some other methods need to be adopted Auxiliary methods for judgment, such as CT image judgment methods, etc. [0003] There are some detection methods of lung lesion tissue in the prior art. For example, the patent document with publication number CN110599448A discloses a lung lesion tissue detection system based on MaskScoring R-CNN network migration learning, which inputs the lung CT to be detected For the image, the network outputs the recognized image, frames and masks the lesion tissue identified by the mask, and mark...

AI Technical Summary

Problems solved by technology

However, during its training, it is necessary to calculate the mask of the lesion area, which requires a lot of resources for marking, and the operation is relatively cumbersome. Therefore, the above method is not suitable for improving the early detection rate of COVID-19. Testing for Novel Coronavirus (COVID-19)