Intelligent Image Analysis and Application of Fiberoptic Bronchoscope in the Treatment of Lobar Pneumonia in Children

The purpose of this study is to explore the application effect of fiberoptic bronchoscopy combined with intelligent image analysis technology in the treatment of lobar pneumonia in children. The subjects were 200 children with lobar pneumonia aged 3 to 14 who were hospitalized from January to December, 2023. They were randomly divided into control group (CG) with traditional treatment and experimental group (EG) with fiberoptic bronchoscopy and intelligent image analysis technology, with 100 cases in each group. On the basis of traditional treatment, EG removes airway secretions through fiberoptic bronchoscopy to observe airway lesions, and uses intelligent image analysis technology based on deep learning algorithm to process and analyze fiberoptic bronchoscopy images in real time to improve the efficiency and accuracy of diagnosis and treatment. The results show that EG is significantly superior to CG in cough relief time, fever reduction time, lung rales disappearance time and hospitalization days. Intelligent image analysis technology shows high accuracy and reliability in lesion identification, secretion quantitative evaluation and airway stenosis degree evaluation, which is highly consistent with the manual measurement results of doctors. In addition, EG is better in safety and tolerance, with low incidence of adverse reactions and high treatment acceptance. The results of this study show that the application of intelligent image analysis technology can significantly improve the efficiency and safety of fiberoptic bronchoscopy in the treatment of lobar pneumonia in children, bring new hope for the rehabilitation of children, and provide a new direction for future research.