摘要
This paper presents a 6-layer customized convolutional neural network model(6L-CNN)to rapidly screen out patients with COVID-19 infection in chest CT images.This model can effectively detect whether the target CT image contains images of pneumonia lesions.In this method,6L-CNN was trained as a binary classifier using the dataset containing CT images of the lung with and without pneumonia as a sample.The results show that the model improves the accuracy of screening out COVID-19 patients.Compared to othermethods,the performance is better.In addition,the method can be extended to other similar clinical conditions.
基金
supported partly by the Open Project of State Key Laboratory of Millimeter Wave under Grant K202218
partly by Innovation and Entrepreneurship Training Program of College Students under Grants 202210700006Y and 202210700005Z。
