1. Improved image-based lung opacity detection of VGG16 model
- Author
-
Ziheng Li, Yupeng Zou, Mingxuan Song, Jiankai Zuo, and Yuelong Zhang
- Subjects
Lung ,Opacity ,Computer science ,business.industry ,Deep learning ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,Pattern recognition ,respiratory system ,Convolutional neural network ,respiratory tract diseases ,ComputingMethodologies_PATTERNRECOGNITION ,medicine.anatomical_structure ,medicine ,Artificial intelligence ,business ,Transfer of learning ,Image based - Abstract
In order to quickly and effectively detect lung information in different medical images, this paper designs an improved VGG16 image-based lung opacity classification detection method based on deep transfer learning. This paper applies offline data enhancement technology to increase the number of samples, improves VGG, and employs transfer learning to train the lung recognition model. The results show that the improved VGG16 network has an accuracy rate of 85% for the classification and recognition of lung pictures, and can accurately detect lung pathological mutation information.
- Published
- 2021