Computerized Tomography Image Feature under Convolutional Neural Network Algorithm Evaluated for Therapeutic Effect of Clarithromycin Combined with Salmeterol/Fluticasone on Chronic Obstructive Pulmonary Disease
| Autor: | Zhaoqiang Yang, Yujian Chen, Cuiying Mo, Anqi Lin, Guoping Luo |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Medicine (General)
Article Subject Biomedical Engineering Health Informatics 02 engineering and technology 030218 nuclear medicine & medical imaging 03 medical and health sciences Pulmonary Disease Chronic Obstructive 0302 clinical medicine R5-920 Clarithromycin 0202 electrical engineering electronic engineering information engineering medicine Medical technology Humans R855-855.5 Fluticasone COPD Bronchus Lung business.industry Therapeutic effect medicine.disease Fluticasone-Salmeterol Drug Combination Bronchodilator Agents respiratory tract diseases medicine.anatomical_structure 020201 artificial intelligence & image processing Surgery Tomography Salmeterol Neural Networks Computer business Tomography X-Ray Computed Algorithm Biotechnology medicine.drug Research Article |
| Zdroj: | Journal of Healthcare Engineering Journal of Healthcare Engineering, Vol 2021 (2021) |
| ISSN: | 2040-2309 2040-2295 |
| Popis: | This study was to explore the use of convolutional neural network (CNN) for the classification and recognition of computerized tomography (CT) images of chronic obstructive pulmonary disease (COPD) and the therapeutic effect of clarithromycin combined with salmeterol/fluticasone. First, the clinical data of COPD patients treated in hospital from September 2018 to December 2020 were collected, and CT and X-ray images were also collected. CT-CNN and X ray-CNN single modal models were constructed based on the LeNet-5 model. The randomized fusion algorithm was introduced to construct a fused CNN model for the diagnosis of COPD patients, and the recognition effect of the model was verified. Subsequently, the three-dimensional reconstruction of the patient’s bronchus was performed using the classified CT images, and the changes of CT quantitative parameters in COPD patients were compared and analyzed. Finally, COPD patients were treated with salmeterol/fluticasone (COPD-C) and combined with clarithromycin (COPD-T). In addition, the differences between patients’ lung function indexes, blood gas indexes, St. George respiratory questionnaire (SGRQ) scores, and the number of acute exacerbations (AECOPD) before and after treatment were evaluated. The results showed that the randomized fusion model under different iteration times and batch sizes always had the highest recognition rate, sensitivity, and specificity compared to the two single modal CNN models, but it also had longer training time. After CT images were used to quantitatively evaluate the changes of the patient’s bronchus, it was found that the area of the upper and lower lung lobes of the affected side of COPD patients and the ratio of the area of the tube wall to the bronchus were significantly changed. The lung function, blood gas index, and SGRQ score of COPD-T patients were significantly improved compared with the COPD-C group ( P < 0.05 ), but there was no considerable difference in AECOPD ( P > 0.05 ). In summary, the randomized fusion-based CNN model can improve the recognition rate of COPD, and salmeterol/fluticasone combined with clarithromycin therapy can significantly improve the clinical treatment effect of COPD patients. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Plný text