Automatic diagnosis algorithm for COVID-19 CT images using improved threshold-based VGG network(PDF)
《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]
- Issue:
- 2022年第6期
- Page:
- 731-736
- Research Field:
- 医学影像物理
- Publishing date:
Info
- Title:
- Automatic diagnosis algorithm for COVID-19 CT images using improved threshold-based VGG network
- Author(s):
- WENG Yujie; LI Zhongxian; JI Yucheng; BO Suling; LIANG Ying
- College of Computer and Information, Inner Mongolia Medical University, Hohhot 010110, China
- Keywords:
- COVID-19 VGG CT image convolutional neural network automatic diagnosis
- PACS:
- R318；R563.1
- DOI:
- DOI:10.3969/j.issn.1005-202X.2022.06.013
- Abstract:
- Lung CT can accurately identify COVID-19, but the workload of doctors is relatively large. An automatic diagnosis algorithm for COVID-19 CT image using improved threshold-based VGG network is proposed. The model can quickly and accurately complete the automatic identification of COVID-19 cases, and provide help for further control of its spread. By comparing VGG-11, VGG-13 and VGG-16 in convolutional neural network VGG, the automatic diagnosis model for COVID-19 CT image with high accuracy is obtained. On this basis, the accuracy is enhanced from 86% to 89% by modifying the threshold, further improving the accuracy of diagnosis.
Last Update: 2022-06-27