Method for Recognition Pneumonia Based on Convolutional Neural Network

• 作者: Dongdong Gao Haijiang Hao Xin Li
• 来源期刊: 国际计算机前沿大会会议论文集
• 学科: 社会科学
• 关键词: Convolutional NEURAL network LUNG FIELD SEGMENTATION PNEUMONIA RECOGNITION
• 年，卷（期）: 2019,（2）
• 页码范围: 155-156
• 页数: 2页
• 分类号: C

摘要

Pneumonia is one of the most common infectious diseases in clinical practice. In the field of pneumonia recognition, traditional algorithms have limitations in feature extraction and scope of application. To solve this problem, a pneumonia recognition is proposed based on convolutional neural network. Firstly, the morphological preprocessing operation was performed on the chest X-ray. Secondly, the convolutional layer containing the 1 * 1 convolution kernel was used instead of a fully connected layer in the convolutional neural network to segment the lung field and obtain the segmentation. The index Dice coefficient can reach 0.948. Finally, a pneumonia recognition model based on convolutional neural network was established. The segmented images were trained and tested. The experimental results show that the average accuracy of the proposed method for pneumonia is up to 96.3%.