Abstract
Objective The study focused on the features of the convolutional neural networks- (CNN-) processed magnetic resonance imaging (MRI) images for plastic bronchitis (PB) in children. Methods 30 PB children were selected as subjects, including 19 boys and 11 girls. They all received the MRI examination for the chest. Then, a CNN-based algorithm was constructed and compared with Active Appearance Model (AAM) algorithm for segmentation effects of MRI images in 30 PB children, factoring into occurring simultaneously than (OST), Dice, and Jaccard coefficient. Results The maximum Dice coefficient of CNN algorithm reached 0.946, while that of active AAM was 0.843, and the Jaccard coefficient of CNN algorithm was also higher (0.894 vs. 0.758, P < 0.05). The MRI images showed pulmonary inflammation in all subjects. Of 30 patients, 14 (46.66%) had complicated pulmonary atelectasis, 9 (30%) had the complicated pleural effusion, 3 (10%) had pneumothorax, 2 (6.67%) had complicated mediastinal emphysema, and 2 (6.67%) had complicated pneumopericardium. Also, of 30 patients, 19 (63.33%) had lung consolidation and atelectasis in a single lung lobe and 11 (36.67%) in both two lung lobes. Conclusion The algorithm based on CNN can significantly improve the segmentation accuracy of MRI images for plastic bronchitis in children. The pleural effusion was a dangerous factor for the occurrence and development of PB.
Highlights
Plastic bronchitis (PB) is a rare respiratory disease arising from pathogenic infections. e endogenous foreign matter produced leads to bronchial congestion, ventilatory disorder, and air exchange dysfunction [1]
Conclusion. e algorithm based on convolutional neural network (CNN) can significantly improve the segmentation accuracy of Magnetic resonance imaging (MRI) images for plastic bronchitis in children. e pleural effusion was a dangerous factor for the occurrence and development of PB
30 PB patients diagnosed in xx Hospital from Jan. 2019 to Dec. 2020 were selected as the subjects, including 19 boys and girls, and they all underwent the MRI examination. ey were between 6 and years old, with an average age of 8.21 ± 1.25 years old. e study was approved by the Ethics Committee of xx
Summary
Plastic bronchitis (PB) is a rare respiratory disease arising from pathogenic infections. e endogenous foreign matter produced leads to bronchial congestion, ventilatory disorder, and air exchange dysfunction [1]. E endogenous foreign matter produced leads to bronchial congestion, ventilatory disorder, and air exchange dysfunction [1]. Plastic bronchitis (PB) is a rare respiratory disease arising from pathogenic infections. It manifests as dyspnea, wheezing, chest pain, fever, and even life-threatening respiratory circulatory failure in severe cases. According to the pathological characteristics, it mainly falls into type I and type II plastic bronchitis. Type I refers to the inflammatory type, where fibrous protein and a great number of inflammatory cells are visible in the bronchus, thanks to infectious diseases of the respiratory tract. Type II is cell-free, where the bronchus is mainly blocked with mucoprotein, without or with just a few infiltration cells, and a great amount of lymph fluid is visible in the alveolus [3]
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